Available Modules

Modules are the building stones of all DSL2 nf-core blocks. You can find more info from nf-core website, if you would like to write your own module.

  • sentieon 17
  • genomics 14
  • rnaseq 13
  • fasta 12
  • index 11
  • alignment 11
  • reference 11
  • genome 9
  • bam 7
  • qc 7
  • single-cell 7
  • gff 6
  • MSA 6
  • scRNA-seq 6
  • splicing 6
  • vsearch 6
  • mirna 6
  • sort 5
  • count 5
  • vcf 4
  • metagenomics 4
  • expression 4
  • dedup 4
  • snp 4
  • differential 4
  • kallisto 4
  • ngscheckmate 4
  • matching 4
  • circrna 4
  • rna 4
  • isomir 4
  • umitools 4
  • assembly 3
  • align 3
  • gtf 3
  • clustering 3
  • metrics 3
  • transcript 3
  • evaluation 3
  • population genetics 3
  • arriba 3
  • fusion 3
  • rsem 3
  • RNA-seq 3
  • amplicon sequences 3
  • RNA 3
  • rna_structure 3
  • variant_calling 3
  • miRNA 3
  • spaceranger 3
  • ambient RNA removal 3
  • fastq 2
  • gatk4 2
  • filter 2
  • merge 2
  • map 2
  • haplotype 2
  • plot 2
  • genotype 2
  • validation 2
  • umi 2
  • mkref 2
  • demultiplexing 2
  • deduplication 2
  • mem 2
  • single cell 2
  • detection 2
  • quantification 2
  • duplication 2
  • popscle 2
  • genotype-based deconvoltion 2
  • CRISPR 2
  • bustools 2
  • nanostring 2
  • nacho 2
  • mRNA 2
  • reformatting 2
  • rrna 2
  • tnhaplotyper2 2
  • mirdeep2 2
  • doublets 2
  • RNA sequencing 2
  • smrnaseq 2
  • varcal 2
  • fusions 2
  • junctions 2
  • RNA-Seq 2
  • splice 2
  • deseq2 2
  • rna-seq 2
  • cram 1
  • statistics 1
  • coverage 1
  • quality control 1
  • download 1
  • nanopore 1
  • contamination 1
  • taxonomy 1
  • convert 1
  • quality 1
  • long reads 1
  • build 1
  • gvcf 1
  • indexing 1
  • QC 1
  • protein 1
  • bqsr 1
  • sequences 1
  • imaging 1
  • mapping 1
  • demultiplex 1
  • base quality score recalibration 1
  • example 1
  • filtering 1
  • cluster 1
  • transcriptome 1
  • bwa 1
  • seqkit 1
  • phasing 1
  • iCLIP 1
  • annotate 1
  • spatial 1
  • extract 1
  • benchmark 1
  • counts 1
  • microbiome 1
  • reference-free 1
  • riboseq 1
  • peak-calling 1
  • CLIP 1
  • interval_list 1
  • haplotypecaller 1
  • happy 1
  • HiFi 1
  • mtDNA 1
  • UMI 1
  • PCA 1
  • mapper 1
  • regions 1
  • eukaryotes 1
  • gene expression 1
  • transposons 1
  • genome assembly 1
  • PacBio 1
  • pseudoalignment 1
  • observations 1
  • k-mer frequency 1
  • barcode 1
  • SimpleAF 1
  • dereplicate 1
  • repeats 1
  • de novo assembler 1
  • salmon 1
  • removal 1
  • assembly evaluation 1
  • allele-specific 1
  • joint genotyping 1
  • version 1
  • eCLIP 1
  • parse 1
  • scatter 1
  • tnfilter 1
  • covariance model 1
  • tnseq 1
  • trio binning 1
  • variancepartition 1
  • dream 1
  • sintax 1
  • vsearch/sort 1
  • usearch 1
  • genome annotation 1
  • trna 1
  • covariance models 1
  • scRNA-Seq 1
  • tnscope 1
  • readwriter 1
  • dnamodelapply 1
  • dnascope 1
  • microRNA 1
  • vsearch/dereplicate 1
  • vsearch/fastqfilter 1
  • fastqfilter 1
  • translate 1
  • HLA 1
  • Computational Immunology 1
  • regtools 1
  • leafcutter 1
  • pdb 1
  • Bioinformatics Tools 1
  • Immune Deconvolution 1
  • doublet_detection 1
  • scvi 1
  • solo 1
  • rna velocity 1
  • ribosomal 1
  • translation 1
  • junction 1
  • genotype-based demultiplexing 1
  • donor deconvolution 1
  • cellsnp 1
  • asereadcounter 1
  • functional genomics 1
  • sgRNA 1
  • CRISPR-Cas9 1
  • maximum-likelihood 1
  • rra 1
  • microrna 1
  • target prediction 1
  • mitochondrial 1
  • haplotype resolution 1
  • readcountssummary 1
  • getpileupsumaries 1
  • kallisto/index 1
  • quant 1
  • germlinevariantsites 1
  • shinyngs 1
  • boxplot 1
  • applyvarcal 1
  • VQSR 1
  • variant recalibration 1
  • exploratory 1
  • density 1
  • polya tail 1
  • fast5 1
  • eucaryotes 1
  • coding 1
  • cds 1
  • transcroder 1
  • features 1
  • rRNA 1
  • ribosomal RNA 1
  • CoPRO 1
  • GRO-cap 1
  • PRO-cap 1
  • CAGE 1
  • NETCAGE 1
  • RAMPAGE 1
  • csRNA-seq 1
  • STRIPE-seq 1
  • PRO-seq 1
  • GRO-seq 1
  • illumina datasets 1
  • phylogenetic composition 1
  • read distribution 1
  • bamstat 1
  • strandedness 1
  • experiment 1
  • read_pairs 1
  • fragment_size 1
  • inner_distance 1
  • sequence-based 1
  • mapping-based 1
  • integrity 1
  • bed 0
  • sam 0
  • annotation 0
  • structural variants 0
  • variant calling 0
  • database 0
  • bacteria 0
  • variants 0
  • classification 0
  • classify 0
  • cnv 0
  • split 0
  • k-mer 0
  • variant 0
  • gfa 0
  • taxonomic profiling 0
  • pacbio 0
  • somatic 0
  • conversion 0
  • proteomics 0
  • binning 0
  • ancient DNA 0
  • VCF 0
  • copy number 0
  • imputation 0
  • phylogeny 0
  • trimming 0
  • contigs 0
  • bedtools 0
  • graph 0
  • kmer 0
  • bisulfite 0
  • bcftools 0
  • mags 0
  • sv 0
  • reporting 0
  • variation graph 0
  • isoseq 0
  • methylation 0
  • visualisation 0
  • databases 0
  • wgs 0
  • bisulphite 0
  • methylseq 0
  • picard 0
  • compression 0
  • long-read 0
  • illumina 0
  • cna 0
  • table 0
  • consensus 0
  • stats 0
  • tsv 0
  • taxonomic classification 0
  • serotype 0
  • phage 0
  • 5mC 0
  • depth 0
  • openms 0
  • antimicrobial resistance 0
  • DNA methylation 0
  • markduplicates 0
  • protein sequence 0
  • repeat 0
  • histogram 0
  • searching 0
  • scWGBS 0
  • pairs 0
  • bins 0
  • samtools 0
  • WGBS 0
  • structure 0
  • pangenome graph 0
  • matrix 0
  • aDNA 0
  • neural network 0
  • amr 0
  • bisulfite sequencing 0
  • mappability 0
  • aligner 0
  • LAST 0
  • completeness 0
  • archaeogenomics 0
  • plink2 0
  • low-coverage 0
  • machine learning 0
  • bcf 0
  • cooler 0
  • damage 0
  • palaeogenomics 0
  • gzip 0
  • germline 0
  • virus 0
  • sequence 0
  • gene 0
  • mmseqs2 0
  • metagenome 0
  • checkm 0
  • db 0
  • biscuit 0
  • decompression 0
  • ncbi 0
  • hmmer 0
  • ucsc 0
  • complexity 0
  • gff3 0
  • feature 0
  • newick 0
  • genotyping 0
  • peaks 0
  • mag 0
  • segmentation 0
  • kraken2 0
  • msa 0
  • blast 0
  • bismark 0
  • glimpse 0
  • hmmsearch 0
  • sketch 0
  • pangenome 0
  • reads 0
  • json 0
  • mitochondria 0
  • cnvkit 0
  • plasmid 0
  • profile 0
  • report 0
  • multiple sequence alignment 0
  • low frequency variant calling 0
  • antimicrobial peptides 0
  • prokaryote 0
  • bedGraph 0
  • short-read 0
  • kmers 0
  • prediction 0
  • single 0
  • NCBI 0
  • duplicates 0
  • antimicrobial resistance genes 0
  • tumor-only 0
  • deamination 0
  • ptr 0
  • diversity 0
  • distance 0
  • visualization 0
  • cat 0
  • isolates 0
  • concatenate 0
  • interval 0
  • amps 0
  • tabular 0
  • fastx 0
  • csv 0
  • de novo 0
  • FASTQ 0
  • text 0
  • mutect2 0
  • arg 0
  • summary 0
  • ont 0
  • fragment 0
  • call 0
  • MAF 0
  • sourmash 0
  • indels 0
  • svtk 0
  • structural 0
  • coptr 0
  • wxs 0
  • antibiotic resistance 0
  • de novo assembly 0
  • compare 0
  • idXML 0
  • adapters 0
  • profiling 0
  • mpileup 0
  • 3-letter genome 0
  • clipping 0
  • merging 0
  • query 0
  • gridss 0
  • view 0
  • ccs 0
  • family 0
  • bedpe 0
  • malt 0
  • preprocessing 0
  • genome assembler 0
  • fai 0
  • bigwig 0
  • read depth 0
  • ampir 0
  • fungi 0
  • dna 0
  • diamond 0
  • microarray 0
  • normalization 0
  • bin 0
  • ganon 0
  • ATAC-seq 0
  • add 0
  • microsatellite 0
  • union 0
  • retrotransposon 0
  • miscoding lesions 0
  • compress 0
  • palaeogenetics 0
  • archaeogenetics 0
  • bgzip 0
  • telomere 0
  • skani 0
  • hic 0
  • deep learning 0
  • paf 0
  • redundancy 0
  • cut 0
  • resistance 0
  • pypgx 0
  • HMM 0
  • enrichment 0
  • chromosome 0
  • gsea 0
  • logratio 0
  • STR 0
  • hybrid capture sequencing 0
  • copy number alteration calling 0
  • chunk 0
  • biosynthetic gene cluster 0
  • bcl2fastq 0
  • propr 0
  • hmmcopy 0
  • image 0
  • DNA sequencing 0
  • parsing 0
  • BGC 0
  • public datasets 0
  • clean 0
  • ranking 0
  • phylogenetic placement 0
  • xeniumranger 0
  • targeted sequencing 0
  • SV 0
  • genmod 0
  • transcriptomics 0
  • DNA sequence 0
  • sample 0
  • abundance 0
  • sequencing 0
  • bedgraph 0
  • containment 0
  • ancestry 0
  • snps 0
  • fgbio 0
  • fcs-gx 0
  • deeparg 0
  • macrel 0
  • mlst 0
  • amplify 0
  • fastk 0
  • das tool 0
  • spark 0
  • html 0
  • structural_variants 0
  • C to T 0
  • DRAMP 0
  • das_tool 0
  • angsd 0
  • insert 0
  • fam 0
  • bim 0
  • SNP 0
  • small indels 0
  • subsample 0
  • pangolin 0
  • panel 0
  • pan-genome 0
  • pairsam 0
  • prokaryotes 0
  • replace 0
  • bacterial 0
  • covid 0
  • benchmarking 0
  • dictionary 0
  • lineage 0
  • polishing 0
  • indel 0
  • fingerprint 0
  • genome mining 0
  • prokka 0
  • typing 0
  • genomes 0
  • neubi 0
  • entrez 0
  • scores 0
  • seqtk 0
  • mcmicro 0
  • aln 0
  • bwameth 0
  • npz 0
  • windowmasker 0
  • hi-c 0
  • bakta 0
  • vrhyme 0
  • nucleotide 0
  • highly_multiplexed_imaging 0
  • mkfastq 0
  • image_analysis 0
  • host 0
  • cellranger 0
  • zip 0
  • unzip 0
  • uncompress 0
  • untar 0
  • mask 0
  • kraken 0
  • microbes 0
  • proteome 0
  • guide tree 0
  • long_read 0
  • somatic variants 0
  • complement 0
  • roh 0
  • transcripts 0
  • organelle 0
  • remove 0
  • converter 0
  • intervals 0
  • gatk4spark 0
  • mzml 0
  • chimeras 0
  • comparisons 0
  • combine 0
  • comparison 0
  • quality trimming 0
  • score 0
  • adapter trimming 0
  • pileup 0
  • bamtools 0
  • bracken 0
  • hidden Markov model 0
  • archiving 0
  • minimap2 0
  • sylph 0
  • amplicon sequencing 0
  • notebook 0
  • reports 0
  • ataqv 0
  • checkv 0
  • informative sites 0
  • kinship 0
  • identity 0
  • relatedness 0
  • repeat expansion 0
  • virulence 0
  • cut up 0
  • krona chart 0
  • survivor 0
  • cool 0
  • dist 0
  • dump 0
  • lossless 0
  • shapeit 0
  • khmer 0
  • krona 0
  • prefetch 0
  • wastewater 0
  • wig 0
  • atac-seq 0
  • tabix 0
  • chip-seq 0
  • ligate 0
  • population genomics 0
  • cfDNA 0
  • uLTRA 0
  • png 0
  • gstama 0
  • profiles 0
  • ichorcna 0
  • mash 0
  • tama 0
  • pigz 0
  • refine 0
  • resolve_bioscience 0
  • gene set 0
  • trancriptome 0
  • gene set analysis 0
  • spatial_transcriptomics 0
  • lofreq 0
  • screen 0
  • krakentools 0
  • phase 0
  • haplotypes 0
  • split_kmers 0
  • interactive 0
  • reformat 0
  • serogroup 0
  • minhash 0
  • GC content 0
  • maximum likelihood 0
  • megan 0
  • polyA_tail 0
  • hla 0
  • primer 0
  • hlala 0
  • hla_typing 0
  • hlala_typing 0
  • iphop 0
  • checksum 0
  • corrupted 0
  • tree 0
  • mapcounter 0
  • haplogroups 0
  • find 0
  • krakenuniq 0
  • instrain 0
  • pair 0
  • long terminal repeat 0
  • trgt 0
  • cgMLST 0
  • regression 0
  • taxids 0
  • taxon name 0
  • zlib 0
  • differential expression 0
  • variation 0
  • vg 0
  • vcflib 0
  • ampgram 0
  • amptransformer 0
  • orthologs 0
  • WGS 0
  • image_processing 0
  • taxon tables 0
  • otu tables 0
  • standardisation 0
  • standardise 0
  • standardization 0
  • svdb 0
  • ome-tif 0
  • small genome 0
  • MCMICRO 0
  • signature 0
  • FracMinHash sketch 0
  • interactions 0
  • functional analysis 0
  • join 0
  • function 0
  • pharokka 0
  • bloom filter 0
  • k-mer index 0
  • COBS 0
  • archive 0
  • xz 0
  • mudskipper 0
  • long terminal retrotransposon 0
  • transcriptomic 0
  • kma 0
  • parallelized 0
  • orthology 0
  • genetics 0
  • rgfa 0
  • small variants 0
  • multiallelic 0
  • nucleotides 0
  • cnvnator 0
  • proportionality 0
  • mitochondrion 0
  • orf 0
  • leviosam2 0
  • lift 0
  • metamaps 0
  • registration 0
  • cancer genomics 0
  • homoploymer 0
  • ped 0
  • Duplication purging 0
  • purge duplications 0
  • library 0
  • preseq 0
  • adapter 0
  • import 0
  • variant pruning 0
  • anndata 0
  • bfiles 0
  • subset 0
  • gene labels 0
  • read-group 0
  • hostile 0
  • duplicate 0
  • decontamination 0
  • GPU-accelerated 0
  • graph layout 0
  • human removal 0
  • screening 0
  • nextclade 0
  • msisensor-pro 0
  • cleaning 0
  • micro-satellite-scan 0
  • tumor 0
  • msi 0
  • instability 0
  • MSI 0
  • Read depth 0
  • contig 0
  • soft-clipped clusters 0
  • snpsift 0
  • snpeff 0
  • effect prediction 0
  • shigella 0
  • switch 0
  • ancient dna 0
  • Streptococcus pneumoniae 0
  • sequenzautils 0
  • transformation 0
  • rename 0
  • salmonella 0
  • Pharmacogenetics 0
  • scaffold 0
  • fixmate 0
  • retrotransposons 0
  • dict 0
  • collate 0
  • bam2fq 0
  • frame-shift correction 0
  • long-read sequencing 0
  • scaffolding 0
  • rtgtools 0
  • sequence analysis 0
  • pharmacogenetics 0
  • runs_of_homozygosity 0
  • polish 0
  • taxonomic profile 0
  • concordance 0
  • duplex 0
  • deconvolution 0
  • bayesian 0
  • merge mate pairs 0
  • reads merging 0
  • short reads 0
  • xenograft 0
  • graft 0
  • unaligned 0
  • fetch 0
  • realignment 0
  • GEO 0
  • trim 0
  • metagenomic 0
  • identifier 0
  • microscopy 0
  • expansionhunterdenovo 0
  • repeat_expansions 0
  • metadata 0
  • tab 0
  • microbial 0
  • emboss 0
  • panelofnormals 0
  • MaltExtract 0
  • HOPS 0
  • authentication 0
  • gatk 0
  • edit distance 0
  • secondary metabolites 0
  • NRPS 0
  • RiPP 0
  • interval list 0
  • evidence 0
  • antibiotics 0
  • antismash 0
  • filtermutectcalls 0
  • simulate 0
  • artic 0
  • aggregate 0
  • demultiplexed reads 0
  • concat 0
  • tbi 0
  • gwas 0
  • CNV 0
  • sra-tools 0
  • settings 0
  • BAM 0
  • blastn 0
  • correction 0
  • calling 0
  • cnv calling 0
  • immunoprofiling 0
  • structural-variant calling 0
  • cvnkit 0
  • estimation 0
  • vdj 0
  • single cells 0
  • genome bins 0
  • recombination 0
  • fasterq-dump 0
  • awk 0
  • intersect 0
  • intersection 0
  • normalize 0
  • norm 0
  • reheader 0
  • eigenstrat 0
  • validate 0
  • samplesheet 0
  • format 0
  • eido 0
  • windows 0
  • metagenomes 0
  • blastp 0
  • region 0
  • heatmap 0
  • sizes 0
  • bases 0
  • spatial_omics 0
  • random forest 0
  • allele 0
  • UMIs 0
  • gem 0
  • ChIP-seq 0
  • baf 0
  • genomad 0
  • getfasta 0
  • derived alleles 0
  • dereplication 0
  • microbial genomics 0
  • jaccard 0
  • overlap 0
  • array_cgh 0
  • cytosure 0
  • decomposeblocksub 0
  • ancestral alleles 0
  • gprofiler2 0
  • gost 0
  • genomecov 0
  • closest 0
  • rad 0
  • bamtobed 0
  • sorting 0
  • structural variant 0
  • bam2fastx 0
  • bam2fastq 0
  • immcantation 0
  • airrseq 0
  • vector 0
  • site frequency spectrum 0
  • immunoinformatics 0
  • f coefficient 0
  • bioawk 0
  • unionBedGraphs 0
  • reverse complement 0
  • simulation 0
  • hmmfetch 0
  • decompose 0
  • pca 0
  • pruning 0
  • subtract 0
  • linkage equilibrium 0
  • slopBed 0
  • transmembrane 0
  • genome graph 0
  • chunking 0
  • homozygous genotypes 0
  • decoy 0
  • heterozygous genotypes 0
  • htseq 0
  • inbreeding 0
  • shiftBed 0
  • multinterval 0
  • sompy 0
  • overlapped bed 0
  • maskfasta 0
  • peak picking 0
  • drep 0
  • homology 0
  • co-orthology 0
  • clumping fastqs 0
  • deduping 0
  • plastid 0
  • smaller fastqs 0
  • resfinder 0
  • resistance genes 0
  • raw 0
  • mgf 0
  • parquet 0
  • parser 0
  • dbsnp 0
  • standardize 0
  • quarto 0
  • masking 0
  • python 0
  • r 0
  • low-complexity 0
  • coexpression 0
  • correlation 0
  • corpcor 0
  • GFF/GTF 0
  • assay 0
  • tandem repeats 0
  • phylogenetics 0
  • minimum_evolution 0
  • parallel 0
  • csi 0
  • Read coverage histogram 0
  • biallelic 0
  • sequence similarity 0
  • spectral clustering 0
  • agat 0
  • longest 0
  • comparative genomics 0
  • isoform 0
  • autozygosity 0
  • homozygosity 0
  • deep variant 0
  • mutect 0
  • idx 0
  • update header 0
  • intron 0
  • md 0
  • transform 0
  • gaps 0
  • introns 0
  • nm 0
  • uq 0
  • install 0
  • joint-genotyping 0
  • genotypegvcf 0
  • BCF 0
  • short 0
  • file manipulation 0
  • plink2_pca 0
  • propd 0
  • verifybamid 0
  • vcf2db 0
  • gemini 0
  • melon 0
  • maf 0
  • lua 0
  • toml 0
  • plant 0
  • vcfbreakmulti 0
  • uniq 0
  • deduplicate 0
  • SINE 0
  • VCFtools 0
  • network 0
  • downsample bam 0
  • DNA contamination estimation 0
  • wget 0
  • mkvdjref 0
  • construct 0
  • graph projection to vcf 0
  • cellpose 0
  • hifi 0
  • extractunbinned 0
  • linkbins 0
  • Assembly 0
  • subsample bam 0
  • downsample 0
  • unmarkduplicates 0
  • bedtobigbed 0
  • genepred 0
  • refflat 0
  • gtftogenepred 0
  • ucsc/liftover 0
  • chromap 0
  • mobile genetic elements 0
  • quality assurnce 0
  • qa 0
  • umicollapse 0
  • snv 0
  • scanner 0
  • crispr 0
  • antibody capture 0
  • files 0
  • antigen capture 0
  • helitron 0
  • multiomics 0
  • remove samples 0
  • upd 0
  • uniparental 0
  • disomy 0
  • domains 0
  • long read alignment 0
  • nucleotide sequence 0
  • copyratios 0
  • comp 0
  • denoisereadcounts 0
  • tblastn 0
  • bedcov 0
  • genome polishing 0
  • groupby 0
  • assembly polishing 0
  • genotype dosages 0
  • vcf file 0
  • postprocessing 0
  • bgen 0
  • subtyping 0
  • chloroplast 0
  • confidence 0
  • blat 0
  • alr 0
  • clr 0
  • Salmonella enterica 0
  • boxcox 0
  • sorted 0
  • bgen file 0
  • Escherichia coli 0
  • createreadcountpanelofnormals 0
  • workflow_mode 0
  • pangenome-scale 0
  • yahs 0
  • all versus all 0
  • mashmap 0
  • wavefront 0
  • whamg 0
  • wham 0
  • compartments 0
  • copy-number 0
  • copy number analysis 0
  • gender determination 0
  • topology 0
  • copy number alterations 0
  • copy number variation 0
  • geo 0
  • workflow 0
  • mapad 0
  • adna 0
  • c to t 0
  • cumulative coverage 0
  • proteus 0
  • readproteingroups 0
  • calder2 0
  • eigenvectors 0
  • hicPCA 0
  • sliding 0
  • cadd 0
  • snakemake 0
  • distance-based 0
  • long read 0
  • homologs 0
  • telseq 0
  • admixture 0
  • taxonomic composition 0
  • mzML 0
  • prepare 0
  • catpack 0
  • multiqc 0
  • mass_error 0
  • search engine 0
  • poolseq 0
  • variant-calling 0
  • stardist 0
  • Staging 0
  • ATACseq 0
  • shift 0
  • ATACshift 0
  • http(s) 0
  • utility 0
  • setgt 0
  • jvarkit 0
  • tar 0
  • tarball 0
  • adapterremoval 0
  • CRISPRi 0
  • tag2tag 0
  • nanoq 0
  • Read filters 0
  • Read trimming 0
  • Read report 0
  • hhsuite 0
  • drug categorization 0
  • ATLAS 0
  • uniques 0
  • Illumina 0
  • functional 0
  • impute-info 0
  • tags 0
  • sequencing_bias 0
  • mkarv 0
  • hashing-based deconvolution 0
  • rank 0
  • 16S 0
  • java 0
  • script 0
  • post mortem damage 0
  • xml 0
  • svg 0
  • standard 0
  • haplotag 0
  • atlas 0
  • staging 0
  • targz 0
  • bias 0
  • scanpy 0
  • nuclear contamination estimate 0
  • resegment 0
  • morphology 0
  • fix 0
  • post Post-processing 0
  • malformed 0
  • partitioning 0
  • chip 0
  • updatedata 0
  • metagenome assembler 0
  • run 0
  • model 0
  • AMPs 0
  • allele counts 0
  • antimicrobial peptide prediction 0
  • plotting 0
  • amp 0
  • recovery 0
  • mgi 0
  • Staphylococcus aureus 0
  • affy 0
  • block substitutions 0
  • reference panels 0
  • relabel 0
  • cell segmentation 0
  • quality_control 0
  • bclconvert 0
  • nucBed 0
  • AT content 0
  • nucleotide content 0
  • elfasta 0
  • elprep 0
  • doublet 0
  • patterns 0
  • controlstatistics 0
  • source tracking 0
  • emoji 0
  • regex 0
  • nuclear segmentation 0
  • paired reads re-pairing 0
  • installation 0
  • barcodes 0
  • doCounts 0
  • subsetting 0
  • logFC 0
  • significance statistic 0
  • p-value 0
  • import segmentation 0
  • redundant 0
  • hmmpress 0
  • identity-by-descent 0
  • go 0
  • scimap 0
  • Bayesian 0
  • host removal 0
  • structural-variants 0
  • omics 0
  • biological activity 0
  • bamtools/split 0
  • prior knowledge 0
  • tag 0
  • cell_barcodes 0
  • haploype 0
  • mygene 0
  • yaml 0
  • associations 0
  • impute 0
  • bedgraphtobigwig 0
  • bamtools/convert 0
  • reference compression 0
  • pile up 0
  • mouse 0
  • reference panel 0
  • bacphlip 0
  • virulent 0
  • nanopore sequencing 0
  • cobra 0
  • spatial_neighborhoods 0
  • Indel 0
  • grea 0
  • seqfu 0
  • multi-tool 0
  • predict 0
  • background_correction 0
  • illumiation_correction 0
  • hardy-weinberg 0
  • hwe statistics 0
  • hwe equilibrium 0
  • reference-independent 0
  • genotype likelihood 0
  • collapse 0
  • liftover 0
  • probabilistic realignment 0
  • n50 0
  • case/control 0
  • cell_type_identification 0
  • cell_phenotyping 0
  • machine_learning 0
  • element 0
  • trimBam 0
  • bamUtil 0
  • shuffleBed 0
  • SNV 0
  • clahe 0
  • refresh 0
  • association 0
  • GWAS 0
  • extension 0
  • temperate 0
  • read group 0
  • cram-size 0
  • bwamem2 0
  • bwameme 0
  • grabix 0
  • 10x 0
  • background 0
  • single-stranded 0
  • regulatory network 0
  • ancientDNA 0
  • transcription factors 0
  • paraphase 0
  • selector 0
  • size 0
  • Pacbio 0
  • quality check 0
  • realign 0
  • circular 0
  • phylogenies 0
  • hmmscan 0
  • spot 0
  • orthogroup 0
  • authentict 0
  • sage 0
  • mass spectrometry 0
  • featuretable 0
  • extraction 0
  • guidetree 0
  • AC/NS/AF 0
  • functional enrichment 0
  • autofluorescence 0
  • paired reads merging 0
  • overlap-based merging 0
  • check 0
  • lifestyle 0
  • hamming-distance 0
  • hashing-based deconvoltion 0
  • gnu 0
  • coreutils 0
  • generic 0
  • transposable element 0
  • retrieval 0
  • cycif 0
  • vcflib/vcffixup 0
  • contiguate 0
  • MMseqs2 0
  • InterProScan 0
  • busco 0
  • droplet based single cells 0
  • antimicrobial reistance 0
  • lexogen 0
  • trimfq 0
  • bigbed 0
  • cmseq 0
  • duplicate removal 0
  • bedtointervallist 0
  • mash/sketch 0
  • calibratedragstrmodel 0
  • reduced 0
  • representations 0
  • maxbin2 0
  • getpileupsummaries 0
  • metagenome-assembled genomes 0
  • cross-samplecontamination 0
  • mass-spectroscopy 0
  • calculatecontamination 0
  • mcr-1 0
  • MD5 0
  • 128 bit 0
  • megahit 0
  • taxonomic assignment 0
  • denovo 0
  • debruijn 0
  • daa 0
  • rma6 0
  • Neisseria meningitidis 0
  • vqsr 0
  • variant quality score recalibration 0
  • 3D heat map 0
  • contour map 0
  • Merqury 0
  • annotateintervals 0
  • targets 0
  • cnnscorevariants 0
  • collectreadcounts 0
  • ploidy 0
  • AMP 0
  • collapsing 0
  • determinegermlinecontigploidy 0
  • legionella 0
  • clinical 0
  • pneumophila 0
  • createsomaticpanelofnormals 0
  • limma 0
  • Listeria monocytogenes 0
  • createsequencedictionary 0
  • condensedepthevidence 0
  • lofreq/call 0
  • lofreq/filter 0
  • qualities 0
  • peptide prediction 0
  • estimate 0
  • dragstr 0
  • composestrtablefile 0
  • short variant discovery 0
  • combinegvcfs 0
  • DNA damage 0
  • NGS 0
  • damage patterns 0
  • collectsvevidence 0
  • smudgeplot 0
  • unionsum 0
  • train 0
  • graph drawing 0
  • SNP table 0
  • contaminant 0
  • single molecule 0
  • cancer genome 0
  • somatic structural variations 0
  • mobile element insertions 0
  • sequencing summary 0
  • NextGenMap 0
  • ngm 0
  • Neisseria gonorrhoeae 0
  • gender 0
  • zipperbams 0
  • graph construction 0
  • ubam 0
  • Beautiful stand-alone HTML report 0
  • squeeze 0
  • odgi 0
  • combine graphs 0
  • graph stats 0
  • graph unchopping 0
  • graph formats 0
  • graph viz 0
  • tumor/normal 0
  • hla-typing 0
  • ILP 0
  • HLA-I 0
  • block-compressed 0
  • unmapped 0
  • GATK UnifiedGenotyper 0
  • bioinformatics tools 0
  • metaphlan 0
  • bootstrapping 0
  • methylation bias 0
  • mbias 0
  • heattree 0
  • gangstr 0
  • assembler 0
  • de Bruijn 0
  • gene-calling 0
  • mitochondrial genome 0
  • reference genome 0
  • gamma 0
  • UShER 0
  • mosdepth 0
  • mitochondrial to nuclear ratio 0
  • otu table 0
  • bacterial variant calling 0
  • germline variant calling 0
  • somatic variant calling 0
  • variant caller 0
  • rust 0
  • microsatellite instability 0
  • fq 0
  • lint 0
  • random 0
  • scan 0
  • mtnucratio 0
  • ratio 0
  • generate 0
  • adapter removal 0
  • spliced 0
  • flip 0
  • txt 0
  • abricate 0
  • amrfinderplus 0
  • fARGene 0
  • rgi 0
  • ibd 0
  • hbd 0
  • beagle 0
  • genome profile 0
  • bgc 0
  • Haemophilus influenzae 0
  • file parsing 0
  • gawk 0
  • extractvariants 0
  • variantrecalibrator 0
  • recalibration model 0
  • variantfiltration 0
  • svcluster 0
  • svannotate 0
  • gccounter 0
  • splitintervals 0
  • readcounter 0
  • splitcram 0
  • site depth 0
  • HMMER 0
  • amino acid 0
  • shiftintervals 0
  • compound 0
  • extract_variants 0
  • Hidden Markov Model 0
  • gene model 0
  • Haplotypes 0
  • Imputation 0
  • joint-variant-calling 0
  • GNU 0
  • merge compare 0
  • genomes on a tree 0
  • low coverage 0
  • gget 0
  • genome statistics 0
  • genome manipulation 0
  • genome summary 0
  • tama_collapse.py 0
  • gfastats 0
  • TAMA 0
  • gvcftools 0
  • Mykrobe 0
  • gstama/merge 0
  • Salmonella Typhi 0
  • repeat content 0
  • gstama/polyacleanup 0
  • GTDB taxonomy 0
  • genome heterozygosity 0
  • genome taxonomy database 0
  • archaea 0
  • genome size 0
  • gunc 0
  • gunzip 0
  • models 0
  • shiftfasta 0
  • hmtnote 0
  • reorder 0
  • Klebsiella 0
  • readorientationartifacts 0
  • learnreadorientationmodel 0
  • indexfeaturefile 0
  • germlinecnvcaller 0
  • germline contig ploidy 0
  • digital normalization 0
  • k-mer counting 0
  • effective genome size 0
  • pneumoniae 0
  • jupytext 0
  • panelofnormalscreation 0
  • kegg 0
  • kofamscan 0
  • jointgenotyping 0
  • combining 0
  • genomicsdbimport 0
  • genomicsdb 0
  • gatherbqsrreports 0
  • tranche filtering 0
  • filtervarianttranches 0
  • filterintervals 0
  • estimatelibrarycomplexity 0
  • duplication metrics 0
  • papermill 0
  • Jupyter 0
  • annotations 0
  • pixel_classification 0
  • shiftchain 0
  • pos 0
  • haemophilus 0
  • selectvariants 0
  • revert 0
  • panel_of_normals 0
  • IDR 0
  • igv 0
  • igv.js 0
  • js 0
  • genome browser 0
  • multicut 0
  • pixel classification 0
  • probability_maps 0
  • Python 0
  • reblockgvcf 0
  • printsvevidence 0
  • printreads 0
  • interproscan 0
  • preprocessintervals 0
  • postprocessgermlinecnvcalls 0
  • genomic islands 0
  • insertion 0
  • snvs 0
  • mutectstats 0
  • mergebamalignment 0
  • leftalignandtrimvariants 0
  • jasminesv 0
  • jasmine 0
  • PCR/optical duplicates 0
  • upper-triangular matrix 0
  • sequencing adapters 0
  • custom 0
  • sertotype 0
  • interleave 0
  • header 0
  • seq 0
  • na 0
  • selection 0
  • random draw 0
  • pseudohaploid 0
  • pseudodiploid 0
  • freqsum 0
  • bam2seqz 0
  • gc_wiggle 0
  • induce 0
  • sex determination 0
  • sequence headers 0
  • genetic sex 0
  • relative coverage 0
  • Cores 0
  • Segmentation 0
  • rare variants 0
  • error 0
  • TMA dearray 0
  • de-novo 0
  • longread 0
  • sha256 0
  • 256 bit 0
  • UNet 0
  • cls 0
  • grep 0
  • scramble 0
  • amplicon 0
  • ampliconclip 0
  • scatterplot 0
  • calmd 0
  • corrrelation 0
  • faidx 0
  • track 0
  • insert size 0
  • repair 0
  • paired 0
  • read pairs 0
  • readgroup 0
  • paired-end 0
  • cluster analysis 0
  • subseq 0
  • clusteridentifier 0
  • peak-caller 0
  • cut&tag 0
  • cut&run 0
  • chromatin 0
  • seacr 0
  • pcr duplicates 0
  • assembly-binning 0
  • cutesv 0
  • gct 0
  • sambamba 0
  • rdtest2vcf 0
  • spatype 0
  • spa 0
  • streptococcus 0
  • sccmec 0
  • variantcalling 0
  • Sample 0
  • protein coding genes 0
  • detecting svs 0
  • short-read sequencing 0
  • polymorphic sites 0
  • svtk/baftest 0
  • baftest 0
  • countsvtypes 0
  • rdtest 0
  • antitarget 0
  • polymorphic 0
  • vcf2bed 0
  • decompress 0
  • polymut 0
  • chromosome_visualization 0
  • Mycobacterium tuberculosis 0
  • chromosomal rearrangements 0
  • access 0
  • fracminhash sketch 0
  • cload 0
  • mcool 0
  • sliding window 0
  • genomic bins 0
  • makebins 0
  • CRAM 0
  • SMN1 0
  • SMN2 0
  • POA 0
  • sniffles 0
  • core 0
  • snippy 0
  • enzyme 0
  • digest 0
  • cooler/balance 0
  • hash sketch 0
  • subcontigs 0
  • dbnsfp 0
  • predictions 0
  • nucleotide composition 0
  • SNPs 0
  • invariant 0
  • constant 0
  • concoct 0
  • partition histograms 0
  • target 0
  • export 0
  • signatures 0
  • duplicate marking 0
  • flagstat 0
  • ligation junctions 0
  • genetic 0
  • deletions 0
  • insertions 0
  • tandem duplications 0
  • ARGs 0
  • picard/renamesampleinvcf 0
  • antibiotic resistance genes 0
  • faqcs 0
  • exclude 0
  • variant identifiers 0
  • str 0
  • indep 0
  • indep pairwise 0
  • recode 0
  • whole genome association 0
  • identifiers 0
  • scoring 0
  • cache 0
  • variant genetic 0
  • sortvcf 0
  • pcr 0
  • porechop_abi 0
  • pbp 0
  • pairtools 0
  • pairstools 0
  • restriction fragments 0
  • select 0
  • groupreads 0
  • duplexumi 0
  • consensus sequence 0
  • public 0
  • paragraph 0
  • graphs 0
  • pbbam 0
  • pbmerge 0
  • subreads 0
  • pair-end 0
  • liftovervcf 0
  • read 0
  • pedigrees 0
  • ENA 0
  • motif 0
  • ChIP-Seq 0
  • phantom peaks 0
  • prophage 0
  • identification 0
  • SRA 0
  • ANI 0
  • hybrid-selection 0
  • mate-pair 0
  • pmdtools 0
  • percent on target 0
  • multimapper 0
  • subsampling 0
  • long uncorrected reads 0
  • rhocall 0
  • R 0
  • escherichia coli 0
  • depth information 0
  • structural variation 0
  • duphold 0
  • PEP 0
  • segment 0
  • rtg 0
  • blastx 0
  • pedfilter 0
  • rocplot 0
  • rtg-tools 0
  • salsa 0
  • salsa2 0
  • LCA 0
  • Ancestor 0
  • neighbour-joining 0
  • quast 0
  • endogenous DNA 0
  • circos 0
  • Streptococcus pyogenes 0
  • swissprot 0
  • genbank 0
  • contact 0
  • pretext 0
  • jpg 0
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  • split by chromosome 0
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  • schema 0
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  • panel of normals 0
  • cutoff 0
  • eklipse 0
  • haplotype purging 0
  • duplicate purging 0
  • false duplications 0
  • assembly curation 0
  • Haplotype purging 0
  • eigenstratdatabasetools 0
  • False duplications 0
  • Assembly curation 0
  • pep 0
  • purging 0
  • integron 0

Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq

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translated_mrna total_mrna translation buffering mrna_abundance rdata fold_change_plot interaction_p_distribution_plot residual_distribution_summary_plot residual_vs_fitted_plot rvm_fit_for_all_contrasts_group_plot rvm_fit_for_interactions_plot rvm_fit_for_omnibus_group_plot simulated_vs_obt_dfbetas_without_interaction_plot session_info versions

anota2seq:

Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq

Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates.

01

extracted_reads_fastq log intermediate_sam intermediate_bam intermediate_sorted_bam versions

arcashla:

arcasHLA performs high resolution genotyping for HLA class I and class II genes from RNA sequencing, supporting both paired and single-end samples.

Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.

metabammeta2fastameta3gtfmeta4blacklistmeta5known_fusionsmeta6structural_variantsmeta7tagsmeta8protein_domains

meta versions fusions fusions_fail

Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.

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fusions fusions_fail versions

arriba:

Fast and accurate gene fusion detection from RNA-Seq data

Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.

0

blacklist cytobands protein_domains known_fusions versions

arriba:

Fast and accurate gene fusion detection from RNA-Seq data

barrnap uses a hmmer profile to find rrnas in reads or contig fasta files

012

gff versions

Module to use CellBender to remove ambient RNA from single-cell RNA-seq data

0123

h5ad versions

cellbender:

CellBender is a software package for eliminating technical artifacts from high-throughput single-cell RNA sequencing (scRNA-seq) data.

Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data

01

h5 filtered_h5 posterior_h5 barcodes metrics report pdf log checkpoint versions

cellbender:

CellBender is a software package for eliminating technical artifacts from high-throughput single-cell RNA sequencing (scRNA-seq) data.

Annotate circRNAs detected in the output from CIRCexplorer2 parse

0100

txt versions

circexplorer2:

Circular RNA analysis toolkits

CIRCexplorer2 parses fusion junction files from multiple aligners to prepare them for CIRCexplorer2 annotate.

01

junction versions

circexplorer2:

Circular RNA analysis toolkit

runs a differential expression analysis with DESeq2

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results dispersion_plot rdata size_factors normalised_counts rlog_counts vst_counts model session_info versions

deseq2:

Differential gene expression analysis based on the negative binomial distribution

Doublet detection in single-cell RNA-seq data

01

h5ad predictions versions

Assessment of duplication rates in RNA-Seq datasets

0101

scatter2d boxplot hist dupmatrix intercept_slope multiqc session_info versions

Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data

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csv versions

gatk4:

Developed in the Data Sciences Platform at the Broad Institute, the toolkit offers a wide variety of tools with a primary focus on variant discovery and genotyping. Its powerful processing engine and high-performance computing features make it capable of taking on projects of any size.

Summarizes counts of reads that support reference, alternate and other alleles for given sites. Results can be used with CalculateContamination. Requires a common germline variant sites file, such as from gnomAD.

012301010100

table versions

gatk4:

Developed in the Data Sciences Platform at the Broad Institute, the toolkit offers a wide variety of tools with a primary focus on variant discovery and genotyping. Its powerful processing engine and high-performance computing features make it capable of taking on projects of any size.

Haplocheck detects contamination patterns in mtDNA AND WGS sequencing studies by analyzing the mitochondrial DNA. Haplocheck also works as a proxy tool for nDNA studies and provides users a graphical report to investigate the contamination further. Internally, it uses the Haplogrep tool, that supports rCRS and RSRS mitochondrial versions.

01

txt html versions

Hap.py is a tool to compare diploid genotypes at haplotype level. Rather than comparing VCF records row by row, hap.py will generate and match alternate sequences in a superlocus. A superlocus is a small region of the genome (sized between 1 and around 1000 bp) that contains one or more variants.

012340101010101

summary_csv roc_all_csv roc_indel_locations_csv roc_indel_locations_pass_csv roc_snp_locations_csv roc_snp_locations_pass_csv extended_csv runinfo metrics_json vcf tbi versions

happy:

Haplotype VCF comparison tools

Whole-genome assembly using PacBio HiFi reads

01201201201

raw_unitigs bin_files processed_unitigs primary_contigs alternate_contigs hap1_contigs hap2_contigs corrected_reads read_overlaps log versions

Align RNA-Seq reads to a reference with HISAT2

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bam summary fastq versions

hisat2:

HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes as well as to a single reference genome.

Builds HISAT2 index for reference genome

010101

index versions

hisat2:

HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes as well as to a single reference genome.

Extracts splicing sites from a gtf files

01

txt versions

hisat2:

HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes as well as to a single reference genome.

Perform immune cell deconvolution using RNA-seq data and various computational methods.

01230

deconv_table deconv_plots versions

Search covariance models against a sequence database

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output alignments target_summary versions

infernal:

Infernal is for searching DNA sequence databases for RNA structure and sequence similarities.

Quantification of transposable elements expression in scRNA-seq

0100

versions results counts log tmp

Create kallisto index

01

index versions

kallisto:

Quantifying abundances of transcripts from bulk and single-cell RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads.

Computes equivalence classes for reads and quantifies abundances

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results json_info log versions

kallisto:

Quantifying abundances of transcripts from RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads.

quantifies scRNA-seq data from fastq files using kb-python.

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count versions matrix

kb:

kallisto and bustools are wrapped in an easy-to-use program called kb

index creation for kb count quantification of single-cell data.

000

versions index t2g cdna intron cdna_t2c intron_t2c

kb:

kallisto|bustools (kb) is a tool developed for fast and efficient processing of single-cell OMICS data.

mageck count for functional genomics, reads are usually mapped to a specific sgRNA

010

count norm versions

mageck:

MAGeCK (Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout), an algorithm to process, QC, analyze and visualize CRISPR screening data.

maximum-likelihood analysis of gene essentialities computation

010

gene_summary sgrna_summary versions

mageck:

MAGeCK (Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout), an algorithm to process, QC, analyze and visualize CRISPR screening data.

Mageck test performs a robust ranking aggregation (RRA) to identify positively or negatively selected genes in functional genomics screens.

01

gene_summary sgrna_summary r_script versions

mageck:

MAGeCK (Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout), an algorithm to process, QC, analyze and visualize CRISPR screening data.

Produces maternal and paternal FastK kmer tables from maternal, paternal and child FastK tables

010101

mat_hap_ktab pat_hap_ktab versions

merquryfk:

FastK based version of Merqury

miRanda is an algorithm for finding genomic targets for microRNAs

010

txt versions

miRDeep2 Mapper is a tool that prepares deep sequencing reads for downstream miRNA detection by collapsing reads, mapping them to a genome, and outputting the required files for miRNA discovery.

0101

outputs versions

mirdeep2:

miRDeep2 Mapper (mapper.pl) is part of the miRDeep2 suite. It collapses identical reads, maps them to a reference genome, and outputs both collapsed FASTA and ARF files for downstream miRNA detection and analysis.

miRDeep2 is a tool for identifying known and novel miRNAs in deep sequencing data by analyzing sequenced RNAs. It integrates the mapping of sequencing reads to the genome and predicts miRNA precursors and mature miRNAs.

012010123

outputs versions

mirdeep2:

miRDeep2 is a tool that discovers microRNA genes by analyzing sequenced RNAs. It includes three main scripts: miRDeep2.pl, mapper.pl, and quantifier.pl for comprehensive miRNA detection and quantification.

mirtop counts generates a file with the minimal information about each sequence and the count data in columns for each samples.

0101012

tsv versions

mirtop:

Small RNA-seq annotation

mirtop export generates files such as fasta, vcf or compatible with isomiRs bioconductor package

0101012

tsv fasta vcf versions

mirtop:

Small RNA-seq annotation

mirtop gff generates the GFF3 adapter format to capture miRNA variations

0101012

gff versions

mirtop:

Small RNA-seq annotation

mirtop gff gets the number of isomiRs and miRNAs annotated in the GFF file by isomiR category.

01

txt log versions

mirtop:

Small RNA-seq annotation

A tool for quality control and tracing taxonomic origins of microRNA sequencing data

0120

html json tsv all_fa rnatype_unknown_fa versions

mirtrace:

miRTrace is a new quality control and taxonomic tracing tool developed specifically for small RNA sequencing data (sRNA-Seq). Each sample is characterized by profiling sequencing quality, read length, sequencing depth and miRNA complexity and also the amounts of miRNAs versus undesirable sequences (derived from tRNAs, rRNAs and sequencing artifacts). In addition to these routine quality control (QC) analyses, miRTrace can accurately and sensitively resolve taxonomic origins of small RNA-Seq data based on the composition of clade-specific miRNAs. This feature can be used to detect cross-clade contaminations in typical lab settings. It can also be applied for more specific applications in forensics, food quality control and clinical diagnosis, for instance tracing the origins of meat products or detecting parasitic microRNAs in host serum.

NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data. NanoString nCounter data is a messenger-RNA/micro-RNA (mRNA/miRNA) expression assay and works with fluorescent barcodes. Each barcode is assigned a mRNA/miRNA, which can be counted after bonding with its target. As a result each count of a specific barcode represents the presence of its target mRNA/miRNA.

0101

normalized_counts normalized_counts_wo_HK versions

NACHO:

R package that uses two main functions to summarize and visualize NanoString RCC files, namely: load_rcc() and visualise(). It also includes a function normalise(), which (re)calculates sample specific size factors and normalises the data. For more information vignette("NACHO") and vignette("NACHO-analysis")

NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data. NanoString nCounter data is a messenger-RNA/micro-RNA (mRNA/miRNA) expression assay and works with fluorescent barcodes. Each barcode is assigned a mRNA/miRNA, which can be counted after bonding with its target. As a result each count of a specific barcode represents the presence of its target mRNA/miRNA.

0101

nacho_qc_reports nacho_qc_png nacho_qc_txt versions

NACHO:

R package that uses two main functions to summarize and visualize NanoString RCC files, namely: load_rcc() and visualise(). It also includes a function normalise(), which (re)calculates sample specific size factors and normalises the data. For more information vignette("NACHO") and vignette("NACHO-analysis")

A tool to quickly download assemblies from NCBI's Assembly database

0000

gbk fna rm features gff faa gpff wgs_gbk cds rna rna_fna report stats versions

Determining whether sequencing data comes from the same individual by using SNP matching. This module generates vaf files for individual fastq file(s), ready for the vafncm module.

0101

vaf versions

ngscheckmate:

NGSCheckMate is a software package for identifying next generation sequencing (NGS) data files from the same individual, including matching between DNA and RNA.

Determining whether sequencing data comes from the same individual by using SNP matching. Designed for humans on vcf or bam files.

010101

corr_matrix matched all pdf vcf versions

ngscheckmate:

NGSCheckMate is a software package for identifying next generation sequencing (NGS) data files from the same individual, including matching between DNA and RNA.

Determining whether sequencing data comes from the same individual by using SNP matching. This module generates PT files from a bed file containing individual positions.

010101

pt versions

ngscheckmate:

NGSCheckMate is a software package for identifying next generation sequencing (NGS) data files from the same individual, including matching between DNA and RNA.

Determining whether sequencing data comes from the same individual by using SNP matching. This module generates PT files from a bed file containing individual positions.

01

pdf corr_matrix all matched versions

ngscheckmate:

NGSCheckMate is a software package for identifying next generation sequencing (NGS) data files from the same individual, including matching between DNA and RNA.

phyloFlash is a pipeline to rapidly reconstruct the SSU rRNAs and explore phylogenetic composition of an illumina (meta)genomic dataset.

0100

results versions

Collect metrics from a RNAseq BAM file

01000

metrics pdf versions

picard:

A set of command line tools (in Java) for manipulating high-throughput sequencing (HTS) data and formats such as SAM/BAM/CRAM and VCF.

Writes an interval list created by splitting a reference at Ns.A Program for breaking up a reference into intervals of alternating regions of N and ACGT bases

010101

intervals versions

picard:

A set of command line tools (in Java) for manipulating high-throughput sequencing (HTS) data and formats such as SAM/BAM/CRAM and VCF.

Main caller script for peak calling

0120

divergent_TREs bidirectional_TREs unidirectional_TREs peakcalling_log versions

pints:

Peak Identifier for Nascent Transcripts Starts (PINTS)

Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded single cell sequencing and external genotyping data for each sample is available.

0123

demuxlet_result versions

popscle:

A suite of population scale analysis tools for single-cell genomics data including implementation of Demuxlet / Freemuxlet methods and auxiliary tools

Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded single cell sequencing and external genotyping data for each sample is not available.

012

result vcf lmix singlet_result singlet_vcf versions

popscle:

A suite of population scale analysis tools for single-cell genomics data including implementation of Demuxlet / Freemuxlet methods and auxiliary tools

Run all Portcullis steps in one go

010101

log pass_junctions_bed pass_junctions_tab intron_gff exon_gff spliced_bam spliced_bai versions

portcullis:

Portcullis is a tool that filters out invalid splice junctions from RNA-seq alignment data. It accepts BAM files from various RNA-seq mappers, analyzes splice junctions and removes likely false positives, outputting filtered results in multiple formats for downstream analysis.

PureCLIP is a tool to detect protein-RNA interaction footprints from single-nucleotide CLIP-seq data, such as iCLIP and eCLIP.

012012010

crosslinks peaks versions

Evaluate alignment data

0101

results versions

qualimap:

Qualimap 2 is a platform-independent application written in Java and R that provides both a Graphical User Interface and a command-line interface to facilitate the quality control of alignment sequencing data and its derivatives like feature counts.

Extract exon-exon junctions from an RNAseq BAM file. The output is a BED file in the BED12 format.

012

junc versions

regtools:

RegTools is a set of tools that integrate DNA-seq and RNA-seq data to help interpret mutations in a regulatory and splicing context.

Ribosomal RNA extraction from a GTF file.

0

rrna_gtf versions

Calculate expression with RSEM

010

counts_gene counts_transcript stat logs versions bam_star bam_genome bam_transcript

rseqc:

RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

Prepare a reference genome for RSEM

00

index transcript_fasta versions

rseqc:

RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

Generate statistics from a bam file

01

txt versions

rseqc:

RSeQC package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data.

Infer strandedness from sequencing reads

010

txt versions

rseqc:

RSeQC package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data.

Calculate inner distance between read pairs.

010

distance freq mean pdf rscript versions

rseqc:

RSeQC package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data.

compare detected splice junctions to reference gene model

010

xls rscript log bed interact_bed pdf events_pdf versions

rseqc:

RSeQC package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data.

compare detected splice junctions to reference gene model

010

pdf rscript versions

rseqc:

RSeQC package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data.

Calculate how mapped reads are distributed over genomic features

010

txt versions

rseqc:

RSeQC package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data.

Calculate read duplication rate

01

seq_xls pos_xls pdf rscript versions

rseqc:

RSeQC package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data.

Calculate TIN (transcript integrity number) from RNA-seq reads

0120

txt xls versions

rseqc:

RSeQC package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data.

Create index for salmon

00

index versions

salmon:

Salmon is a tool for wicked-fast transcript quantification from RNA-seq data

gene/transcript quantification with Salmon

0100000

results json_info lib_format_counts versions

salmon:

Salmon is a tool for wicked-fast transcript quantification from RNA-seq data

Module to use scAR to remove ambient RNA from single-cell RNA-seq data

012

h5ad versions

scvitools:

scvi-tools (single-cell variational inference tools) is a package for end-to-end analysis of single-cell omics data

scar:

scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics.

Detect doublets in single-cell RNA-Seq data

01

h5ad predictions versions

scvitools:

A scalable toolkit for probabilistic modeling applied to single-cell omics data

A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection

0100

alignment trans_alignments multi_bed single_bed versions

segemehl:

A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection

Generate genome indices for segemehl align

0

index versions

segemehl:

A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection

Apply a score cutoff to filter variants based on a recalibration table. Sentieon's Aplyvarcal performs the second pass in a two-stage process called Variant Quality Score Recalibration (VQSR). Specifically, it applies filtering to the input variants based on the recalibration table produced in the previous step VarCal and a target sensitivity value. https://support.sentieon.com/manual/usages/general/#applyvarcal-algorithm

0123450101

vcf tbi versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

Create BWA index for reference genome

01

index versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

Performs fastq alignment to a fasta reference using Sentieon's BWA MEM

01010101

bam_and_bai versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

Accelerated implementation of the Picard CollectVariantCallingMetrics tool.

012012010101

metrics summary versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

Accelerated implementation of the GATK DepthOfCoverage tool.

01201010101

per_locus sample_summary statistics coverage_counts coverage_proportions interval_summary versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

Collects multiple quality metrics from a bam file

01201010

mq_metrics qd_metrics gc_summary gc_metrics aln_metrics is_metrics mq_plot qd_plot is_plot gc_plot versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

Runs the sentieon tool LocusCollector followed by Dedup. LocusCollector collects read information that is used by Dedup which in turn marks or removes duplicate reads.

0120101

cram crai bam bai score metrics metrics_multiqc_tsv versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

modifies the input VCF file by adding the MLrejected FILTER to the variants

012010101

vcf index versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

DNAscope algorithm performs an improved version of Haplotype variant calling.

01230101010101000

vcf vcf_tbi gvcf gvcf_tbi versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

Perform joint genotyping on one or more samples pre-called with Sentieon's Haplotyper.

012301010101

vcf_gz vcf_gz_tbi versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

Runs Sentieon's haplotyper for germline variant calling.

012340101010100

vcf vcf_tbi gvcf gvcf_tbi versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

Generate recalibration table and optionally perform base quality recalibration

01201010101010

table table_post recal_alignment csv pdf versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

Merges BAM files, and/or convert them into cram files. Also, outputs the result of applying the Base Quality Score Recalibration to a file.

0120101

output index output_index versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

Filters the raw output of sentieon/tnhaplotyper2.

01234560101

vcf vcf_tbi stats versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

Tnhaplotyper2 performs somatic variant calling on the tumor-normal matched pairs.

01230101010101010100

orientation_data contamination_data contamination_segments stats vcf index versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

TNscope algorithm performs somatic variant calling on the tumor-normal matched pair or the tumor only data, using a Haplotyper algorithm.

012010101201201201

vcf index versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

Module for Sentieons VarCal. The VarCal algorithm calculates the Variant Quality Score Recalibration (VQSR). VarCal builds a recalibration model for scoring variant quality. https://support.sentieon.com/manual/usages/general/#varcal-algorithm

01200000

recal idx tranches plots versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

Collects whole genome quality metrics from a bam file

012010101

wgs_metrics versions

sentieon:

Sentieonยฎ provides complete solutions for secondary DNA/RNA analysis for a variety of sequencing platforms, including short and long reads. Our software improves upon BWA, STAR, Minimap2, GATK, HaplotypeCaller, Mutect, and Mutect2 based pipelines and is deployable on any generic-CPU-based computing system.

Seqcluster collapse reduces computational complexity by collapsing identical sequences in a FASTQ file.

01

fastq versions

seqcluster:

Small RNA analysis from NGS data. Seqcluster generates a list of clusters of small RNA sequences, their genome location, their annotation and the abundance in all the sample of the project.

Translate DNA/RNA to protein sequence

01

fastx versions

seqkit:

A cross-platform and ultrafast toolkit for FASTA/Q file manipulation

build and deploy Shiny apps for interactively mining differential abundance data

01230120

app versions

shinyngs:

Provides Shiny applications for various array and NGS applications. Currently very RNA-seq centric, with plans for expansion.

Make plots for interpretation of differential abundance statistics

010123

volcanos_png volcanos_html versions

shinyngs:

Provides Shiny applications for various array and NGS applications. Currently very RNA-seq centric, with plans for expansion.

Make exploratory plots for analysis of matrix data, including PCA, Boxplots and density plots

0123

boxplots_png boxplots_html densities_png densities_html pca2d_png pca2d_html pca3d_png pca3d_html mad_png mad_html dendro versions

shinyngs:

Provides Shiny applications for various array and NGS applications. Currently very RNA-seq centric, with plans for expansion.

validate consistency of feature and sample annotations with matrices and contrasts

0120101

sample_meta feature_meta assays contrasts versions

shinyngs:

Provides Shiny applications for various array and NGS applications. Currently very RNA-seq centric, with plans for expansion.

Indexing of transcriptome for gene expression quantification using SimpleAF

012010101

index ref t2g versions

simpleaf:

SimpleAF is a tool for quantification of gene expression from RNA-seq data

Local sequence alignment tool for filtering, mapping and clustering.

010101

reads log index versions

SortMeRNA:

The core algorithm is based on approximate seeds and allows for sensitive analysis of NGS reads. The main application of SortMeRNA is filtering rRNA from metatranscriptomic data. SortMeRNA takes as input files of reads (fasta, fastq, fasta.gz, fastq.gz) and one or multiple rRNA database file(s), and sorts apart aligned and rejected reads into two files. Additional applications include clustering and taxonomy assignation available through QIIME v1.9.1. SortMeRNA works with Illumina, Ion Torrent and PacBio data, and can produce SAM and BLAST-like alignments.

Module to use the 10x Space Ranger pipeline to process 10x spatial transcriptomics data

012345678900

outs versions

spaceranger:

Visium Spatial Gene Expression is a next-generation molecular profiling solution for classifying tissue based on total mRNA. Space Ranger is a set of analysis pipelines that process Visium Spatial Gene Expression data with brightfield and fluorescence microscope images. Space Ranger allows users to map the whole transcriptome in formalin fixed paraffin embedded (FFPE) and fresh frozen tissues to discover novel insights into normal development, disease pathology, and clinical translational research. Space Ranger provides pipelines for end to end analysis of Visium Spatial Gene Expression experiments.

Module to build a filtered GTF needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkgtf command.

0

gtf versions

spaceranger:

Visium Spatial Gene Expression is a next-generation molecular profiling solution for classifying tissue based on total mRNA. Space Ranger is a set of analysis pipelines that process Visium Spatial Gene Expression data with brightfield and fluorescence microscope images. Space Ranger allows users to map the whole transcriptome in formalin fixed paraffin embedded (FFPE) and fresh frozen tissues to discover novel insights into normal development, disease pathology, and clinical translational research. Space Ranger provides pipelines for end to end analysis of Visium Spatial Gene Expression experiments.

Module to build the reference needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkref command.

000

reference versions

spaceranger:

Visium Spatial Gene Expression is a next-generation molecular profiling solution for classifying tissue based on total mRNA. Space Ranger is a set of analysis pipelines that process Visium Spatial Gene Expression data with brightfield and fluorescence microscope images. Space Ranger allows users to map the whole transcriptome in formalin fixed paraffin embedded (FFPE) and fresh frozen tissues to discover novel insights into normal development, disease pathology, and clinical translational research. Space Ranger provides pipelines for end to end analysis of Visium Spatial Gene Expression experiments.

Get the minimal allowed index version from STAR

NO input

index_version versions

star:

STAR is a software package for mapping DNA sequences against a large reference genome, such as the human genome.

Merges the annotation gtf file and the stringtie output gtf files

00

gtf versions

stringtie2:

Transcript assembly and quantification for RNA-Seq

Transcript assembly and quantification for RNA-Se

010

transcript_gtf abundance coverage_gtf ballgown versions

stringtie2:

Transcript assembly and quantification for RNA-Seq

Count reads that map to genomic features

012

counts summary versions

featurecounts:

featureCounts is a highly efficient general-purpose read summarization program that counts mapped reads for genomic features such as genes, exons, promoter, gene bodies, genomic bins and chromosomal locations. It can be used to count both RNA-seq and genomic DNA-seq reads.

Estimating poly(A)-tail lengths from basecalled fast5 files produced by Nanopore sequencing of RNA and DNA

01

csv_gz versions

Aligns sequences using T_COFFEE

01010120

alignment lib versions

tcoffee:

A collection of tools for Computing, Evaluating and Manipulating Multiple Alignments of DNA, RNA, Protein Sequences and Structures.

pigz:

Parallel implementation of the gzip algorithm.

Compares 2 alternative MSAs to evaluate them.

012

scores versions

tcoffee:

A collection of tools for Multiple Alignments of DNA, RNA, Protein Sequence

pigz:

Parallel implementation of the gzip algorithm.

Computes a consensus alignment using T_COFFEE

01010

alignment eval versions

tcoffee:

A collection of tools for Computing, Evaluating and Manipulating Multiple Alignments of DNA, RNA, Protein Sequences and Structures.

pigz:

Parallel implementation of the gzip algorithm.

Reformats the header of PDB files with t-coffee

01

formatted_pdb versions

tcoffee:

A collection of tools for Computing, Evaluating and Manipulating Multiple Alignments of DNA, RNA, Protein Sequences and Structures.

Computes the irmsd score for a given alignment and the structures.

01012

irmsd versions

tcoffee:

A collection of tools for Multiple Alignments of DNA, RNA, Protein Sequence

pigz:

Parallel implementation of the gzip algorithm.

Aligns sequences using the regressive algorithm as implemented in the T_COFFEE package

01010120

alignment versions

tcoffee:

A collection of tools for Computing, Evaluating and Manipulating Multiple Alignments of DNA, RNA, Protein Sequences and Structures.

pigz:

Parallel implementation of the gzip algorithm.

Reformats files with t-coffee

01

formatted_file versions

tcoffee:

A collection of tools for Computing, Evaluating and Manipulating Multiple Alignments of DNA, RNA, Protein Sequences and Structures.

Compute the TCS score for a MSA or for a MSA plus a library file. Outputs the tcs as it is and a csv with just the total TCS score.

0101

tcs scores versions

tcoffee:

A collection of tools for Multiple Alignments of DNA, RNA, Protein Sequence

pigz:

Parallel implementation of the gzip algorithm.

TransDecoder identifies candidate coding regions within transcript sequences. it is used to build gff file.

01

pep gff3 cds dat folder versions

transdecoder:

TransDecoder identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Seq transcript assembly using Trinity, or constructed based on RNA-Seq alignments to the genome using Tophat and Cufflinks.

TransDecoder identifies candidate coding regions within transcript sequences. It is used to build gff file. You can use this module after transdecoder_longorf

010

pep gff3 cds bed versions

transdecoder:

TransDecoder identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Seq transcript assembly using Trinity, or constructed based on RNA-Seq alignments to the genome using Tophat and Cufflinks.

Assembles a de novo transcriptome from RNAseq reads

01

transcript_fasta log versions

Detection of tRNA sequences using covariance models

01

tsv log stats fasta gff bed versions

Run TRUST4 on RNA-seq data

01201010101

tsv airr_files airr_tsv report_tsv fasta out fq outs versions

Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read.

0120

bam log tsv_edit_distance tsv_per_umi tsv_umi_per_position versions

umi_tools:

UMI-tools contains tools for dealing with Unique Molecular Identifiers (UMIs)/Random Molecular Tags (RMTs) and single cell RNA-Seq cell barcodes

Extracts UMI barcode from a read and add it to the read name, leaving any sample barcode in place

01

reads log versions

umi_tools:

UMI-tools contains tools for dealing with Unique Molecular Identifiers (UMIs)/Random Molecular Tags (RMTs) and single cell RNA-Seq cell barcodes

Group reads based on their UMI and mapping coordinates

01200

log bam tsv versions

umi_tools:

UMI-tools contains tools for dealing with Unique Molecular Identifiers (UMIs)/Random Molecular Tags (RMTs) and single cell RNA-Seq cell barcodes

Make the output from umi_tools dedup or group compatible with RSEM

012

bam log versions

umi_tools:

UMI-tools contains tools for dealing with Unique Molecular Identifiers (UMIs)/Random Molecular Tags (RMTs) and single cell RNA-Seq cell barcodes

Module to run UniverSC an open-source pipeline to demultiplex and process single-cell RNA-Seq data

010

outs versions

Runs a differential expression analysis with dream() from variancePartition R package

01234012

results model versions

dream:

Differential expression for repeated measures

Velocyto is a library for the analysis of RNA velocity. velocyto.py CLI use Path(resolve_path=True) and breaks the nextflow logic of symbolic links. If in the work dir velocyto find a file named EXACTLY cellsorted_[ORIGINAL_BAM_NAME] it will skip the samtools sort step. Cellsorted bam file should be cell sorted with:

    samtools sort -t CB -O BAM -o cellsorted_input.bam input.bam

See module test for an example with the SAMTOOLS_SORT nf-core module. Config example to cellsort input bam using SAMTOOLS_SORT:

    withName: SAMTOOLS_SORT {
        ext.prefix = { "cellsorted_${bam.baseName}" }
        ext.args = '-t CB -O BAM'
    }

Optional mask must be passed with ext.args and option --mask This is why I need to stage in the work dir 2 bam files (cellsorted and original). See also velocyto tutorial

01230

loom versions

calculate secondary structures of two RNAs with dimerization

01

rnacofold_csv rnacofold_ps versions

viennarna:

calculate secondary structures of two RNAs with dimerization

The program works much like RNAfold, but allows one to specify two RNA sequences which are then allowed to form a dimer structure. RNA sequences are read from stdin in the usual format, i.e. each line of input corresponds to one sequence, except for lines starting with > which contain the name of the next sequence. To compute the hybrid structure of two molecules, the two sequences must be concatenated using the & character as separator. RNAcofold can compute minimum free energy (mfe) structures, as well as partition function (pf) and base pairing probability matrix (using the -p switch) Since dimer formation is concentration dependent, RNAcofold can be used to compute equilibrium concentrations for all five monomer and (homo/hetero)-dimer species, given input concentrations for the monomers. Output consists of the mfe structure in bracket notation as well as PostScript structure plots and โ€œdot plotโ€ files containing the pair probabilities, see the RNAfold man page for details. In the dot plots a cross marks the chain break between the two concatenated sequences. The program will continue to read new sequences until a line consisting of the single character @ or an end of file condition is encountered.

Predict RNA secondary structure using the ViennaRNA RNAfold tools. Calculate minimum free energy secondary structures and partition function of RNAs.

01

rnafold_txt rnafold_ps versions

viennarna:

Calculate minimum free energy secondary structures and partition function of RNAs

The program reads RNA sequences, calculates their minimum free energy (mfe) structure and prints the mfe structure in bracket notation and its free energy. If not specified differently using commandline arguments, input is accepted from stdin or read from an input file, and output printed to stdout. If the -p option was given it also computes the partition function (pf) and base pairing probability matrix, and prints the free energy of the thermodynamic ensemble, the frequency of the mfe structure in the ensemble, and the ensemble diversity to stdout.

calculate locally stable secondary structures of RNAs

0

rnalfold_txt versions

viennarna:

calculate locally stable secondary structures of RNAs

Compute locally stable RNA secondary structure with a maximal base pair span. For a sequence of length n and a base pair span of L the algorithm uses only O(n+LL) memory and O(nL*L) CPU time. Thus it is practical to โ€œscanโ€ very large genomes for short RNA structures. Output consists of a list of secondary structure components of size <= L, one entry per line. Each output line contains the predicted local structure its energy in kcal/mol and the starting position of the local structure.

Use vireo to perform donor deconvolution for multiplexed scRNA-seq data

01234

summary donor_ids prob_singlets prob_doublets versions

Cluster sequences using a single-pass, greedy centroid-based clustering algorithm.

01

aln biom mothur otu bam out blast uc centroids clusters profile msa versions

vsearch:

VSEARCH is a versatile open-source tool for microbiome analysis, including chimera detection, clustering, dereplication and rereplication, extraction, FASTA/FASTQ/SFF file processing, masking, orienting, pair-wise alignment, restriction site cutting, searching, shuffling, sorting, subsampling, and taxonomic classification of amplicon sequences for metagenomics, genomics, and population genetics. (USEARCH alternative)

Merge strictly identical sequences contained in filename. Identical sequences are defined as having the same length and the same string of nucleotides (case insensitive, T and U are considered the same).

01

fasta clustering log versions

vsearch:

A versatile open source tool for metagenomics (USEARCH alternative)

Performs quality filtering and / or conversion of a FASTQ file to FASTA format.

01

fasta log versions

vsearch:

VSEARCH is a versatile open-source tool for microbiome analysis, including chimera detection, clustering, dereplication and rereplication, extraction, FASTA/FASTQ/SFF file processing, masking, orienting, pair-wise alignment, restriction site cutting, searching, shuffling, sorting, subsampling, and taxonomic classification of amplicon sequences for metagenomics, genomics, and population genetics. (USEARCH alternative)

Taxonomic classification using the sintax algorithm.

010

tsv versions

vsearch:

VSEARCH is a versatile open-source tool for microbiome analysis, including chimera detection, clustering, dereplication and rereplication, extraction, FASTA/FASTQ/SFF file processing, masking, orienting, pair-wise alignment, restriction site cutting, searching, shuffling, sorting, subsampling, and taxonomic classification of amplicon sequences for metagenomics, genomics, and population genetics. (USEARCH alternative)

Sort fasta entries by decreasing abundance (--sortbysize) or sequence length (--sortbylength).

010

fasta versions

vsearch:

VSEARCH is a versatile open-source tool for microbiome analysis, including chimera detection, clustering, dereplication and rereplication, extraction, FASTA/FASTQ/SFF file processing, masking, orienting, pair-wise alignment, restriction site cutting, searching, shuffling, sorting, subsampling, and taxonomic classification of amplicon sequences for metagenomics, genomics, and population genetics. (USEARCH alternative)

Compare target sequences to fasta-formatted query sequences using global pairwise alignment.

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aln biom lca mothur otu sam tsv txt uc versions

vsearch:

VSEARCH is a versatile open-source tool for microbiome analysis, including chimera detection, clustering, dereplication and rereplication, extraction, FASTA/FASTQ/SFF file processing, masking, orienting, pair-wise alignment, restriction site cutting, searching, shuffling, sorting, subsampling, and taxonomic classification of amplicon sequences for metagenomics, genomics, and population genetics. (USEARCH alternative)

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