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.

  • copy number 14
  • cnv 13
  • cna 10
  • somatic 6
  • tumor-only 6
  • single 6
  • cnvkit 6
  • bam 5
  • fasta 4
  • DNA sequencing 4
  • targeted sequencing 4
  • hybrid capture sequencing 4
  • copy number alteration calling 4
  • gatk4 3
  • npz 3
  • reference 2
  • cram 2
  • wgs 2
  • cfDNA 2
  • cnvnator 2
  • ichorcna 2
  • sequenzautils 2
  • cvnkit 2
  • bed 1
  • counts 1
  • png 1
  • copyratios 1
  • BAM 1
  • copy number variation 1
  • modelsegments 1
  • copy-number 1
  • copy number analysis 1
  • gender determination 1
  • copy number alterations 1
  • determinegermlinecontigploidy 1
  • postprocessgermlinecnvcalls 1
  • target 1
  • export 1
  • antitarget 1
  • access 1
  • normal database 1
  • panel of normals 1
  • genomic intervals 1
  • intervals coverage 1
  • gc_wiggle 1
  • bam2seqz 1
  • SMN1 1
  • SMN2 1
  • CRAM 1
  • panel_of_normals 1
  • genomics 0
  • vcf 0
  • fastq 0
  • metagenomics 0
  • genome 0
  • index 0
  • alignment 0
  • assembly 0
  • sort 0
  • sam 0
  • annotation 0
  • structural variants 0
  • variant calling 0
  • database 0
  • filter 0
  • align 0
  • merge 0
  • gff 0
  • bacteria 0
  • map 0
  • coverage 0
  • statistics 0
  • variants 0
  • qc 0
  • quality control 0
  • classification 0
  • nanopore 0
  • download 0
  • gtf 0
  • classify 0
  • k-mer 0
  • variant 0
  • split 0
  • MSA 0
  • taxonomy 0
  • taxonomic profiling 0
  • gfa 0
  • contamination 0
  • sentieon 0
  • pacbio 0
  • convert 0
  • conversion 0
  • clustering 0
  • quality 0
  • count 0
  • binning 0
  • proteomics 0
  • VCF 0
  • ancient DNA 0
  • single-cell 0
  • bedtools 0
  • phylogeny 0
  • contigs 0
  • rnaseq 0
  • long reads 0
  • imputation 0
  • trimming 0
  • build 0
  • reporting 0
  • consensus 0
  • gvcf 0
  • isoseq 0
  • sv 0
  • bcftools 0
  • mags 0
  • kmer 0
  • variation graph 0
  • bisulfite 0
  • graph 0
  • picard 0
  • bisulphite 0
  • compression 0
  • table 0
  • methylseq 0
  • indexing 0
  • long-read 0
  • visualisation 0
  • illumina 0
  • protein 0
  • bqsr 0
  • databases 0
  • QC 0
  • methylation 0
  • stats 0
  • phage 0
  • sequences 0
  • demultiplex 0
  • mapping 0
  • openms 0
  • imaging 0
  • plink2 0
  • 5mC 0
  • serotype 0
  • taxonomic classification 0
  • metrics 0
  • antimicrobial resistance 0
  • depth 0
  • tsv 0
  • haplotype 0
  • pangenome graph 0
  • markduplicates 0
  • histogram 0
  • neural network 0
  • structure 0
  • cluster 0
  • base quality score recalibration 0
  • scWGBS 0
  • samtools 0
  • matrix 0
  • WGBS 0
  • expression 0
  • plot 0
  • amr 0
  • protein sequence 0
  • pairs 0
  • searching 0
  • DNA methylation 0
  • filtering 0
  • example 0
  • repeat 0
  • aDNA 0
  • bins 0
  • machine learning 0
  • validation 0
  • mmseqs2 0
  • bcf 0
  • completeness 0
  • low-coverage 0
  • mappability 0
  • phasing 0
  • biscuit 0
  • transcript 0
  • annotate 0
  • checkm 0
  • virus 0
  • metagenome 0
  • gzip 0
  • aligner 0
  • palaeogenomics 0
  • cooler 0
  • sequence 0
  • LAST 0
  • transcriptome 0
  • gene 0
  • bwa 0
  • genotype 0
  • seqkit 0
  • archaeogenomics 0
  • damage 0
  • iCLIP 0
  • germline 0
  • bisulfite sequencing 0
  • db 0
  • complexity 0
  • evaluation 0
  • genotyping 0
  • feature 0
  • peaks 0
  • gff3 0
  • kraken2 0
  • hmmer 0
  • mkref 0
  • segmentation 0
  • blast 0
  • decompression 0
  • ncbi 0
  • glimpse 0
  • population genetics 0
  • msa 0
  • spatial 0
  • newick 0
  • ucsc 0
  • umi 0
  • mag 0
  • bismark 0
  • hmmsearch 0
  • dedup 0
  • sketch 0
  • vsearch 0
  • prokaryote 0
  • reads 0
  • demultiplexing 0
  • antimicrobial resistance genes 0
  • rna 0
  • csv 0
  • extract 0
  • bedGraph 0
  • multiple sequence alignment 0
  • short-read 0
  • deduplication 0
  • report 0
  • NCBI 0
  • duplicates 0
  • mirna 0
  • snp 0
  • plasmid 0
  • pangenome 0
  • antimicrobial peptides 0
  • prediction 0
  • splicing 0
  • scRNA-seq 0
  • json 0
  • low frequency variant calling 0
  • mitochondria 0
  • kmers 0
  • profile 0
  • differential 0
  • mpileup 0
  • idXML 0
  • concatenate 0
  • fragment 0
  • diversity 0
  • profiling 0
  • svtk 0
  • mem 0
  • cat 0
  • kallisto 0
  • detection 0
  • riboseq 0
  • fastx 0
  • summary 0
  • text 0
  • benchmark 0
  • MAF 0
  • gridss 0
  • adapters 0
  • merging 0
  • isolates 0
  • arg 0
  • compare 0
  • amps 0
  • indels 0
  • antibiotic resistance 0
  • interval 0
  • sourmash 0
  • mutect2 0
  • call 0
  • FASTQ 0
  • microbiome 0
  • visualization 0
  • ptr 0
  • ont 0
  • de novo assembly 0
  • query 0
  • distance 0
  • tabular 0
  • view 0
  • reference-free 0
  • wxs 0
  • de novo 0
  • clipping 0
  • structural 0
  • single cell 0
  • deamination 0
  • 3-letter genome 0
  • coptr 0
  • microsatellite 0
  • deep learning 0
  • gsea 0
  • snps 0
  • haplotypecaller 0
  • mtDNA 0
  • enrichment 0
  • fgbio 0
  • redundancy 0
  • quantification 0
  • CLIP 0
  • read depth 0
  • transcriptomics 0
  • peak-calling 0
  • xeniumranger 0
  • diamond 0
  • circrna 0
  • miscoding lesions 0
  • palaeogenetics 0
  • bedgraph 0
  • ranking 0
  • interval_list 0
  • HiFi 0
  • happy 0
  • public datasets 0
  • preprocessing 0
  • genome assembler 0
  • hic 0
  • bin 0
  • bigwig 0
  • retrotransposon 0
  • STR 0
  • archaeogenetics 0
  • cut 0
  • ganon 0
  • phylogenetic placement 0
  • containment 0
  • SV 0
  • sylph 0
  • isomir 0
  • bedpe 0
  • dna 0
  • ngscheckmate 0
  • HMM 0
  • hmmcopy 0
  • paf 0
  • telomere 0
  • pypgx 0
  • compress 0
  • matching 0
  • ccs 0
  • genmod 0
  • resistance 0
  • BGC 0
  • chunk 0
  • propr 0
  • fai 0
  • image 0
  • bgzip 0
  • biosynthetic gene cluster 0
  • malt 0
  • clean 0
  • abundance 0
  • chromosome 0
  • fungi 0
  • DNA sequence 0
  • fusion 0
  • ATAC-seq 0
  • umitools 0
  • bcl2fastq 0
  • ampir 0
  • normalization 0
  • logratio 0
  • union 0
  • ancestry 0
  • add 0
  • sample 0
  • sequencing 0
  • microarray 0
  • skani 0
  • family 0
  • parsing 0
  • untar 0
  • transposons 0
  • highly_multiplexed_imaging 0
  • unzip 0
  • fastk 0
  • mcmicro 0
  • image_analysis 0
  • duplication 0
  • fusions 0
  • UMI 0
  • uncompress 0
  • html 0
  • ataqv 0
  • krona 0
  • bacterial 0
  • bakta 0
  • benchmarking 0
  • minimap2 0
  • pileup 0
  • tabix 0
  • quality trimming 0
  • zip 0
  • archiving 0
  • polishing 0
  • remove 0
  • entrez 0
  • panel 0
  • adapter trimming 0
  • uLTRA 0
  • scaffolding 0
  • small indels 0
  • host 0
  • typing 0
  • bamtools 0
  • checkv 0
  • khmer 0
  • informative sites 0
  • spaceranger 0
  • popscle 0
  • genotype-based deconvoltion 0
  • observations 0
  • chimeras 0
  • lossless 0
  • DRAMP 0
  • neubi 0
  • amplify 0
  • macrel 0
  • kinship 0
  • PacBio 0
  • ligate 0
  • rna_structure 0
  • RNA 0
  • virulence 0
  • identity 0
  • dist 0
  • transcripts 0
  • genome assembly 0
  • relatedness 0
  • score 0
  • angsd 0
  • shapeit 0
  • seqtk 0
  • RNA-seq 0
  • subsample 0
  • pseudoalignment 0
  • SNP 0
  • arriba 0
  • krona chart 0
  • rsem 0
  • reports 0
  • notebook 0
  • wastewater 0
  • amplicon sequencing 0
  • indel 0
  • dictionary 0
  • miRNA 0
  • eukaryotes 0
  • prokaryotes 0
  • spark 0
  • survivor 0
  • population genomics 0
  • genome mining 0
  • hidden Markov model 0
  • mask 0
  • ambient RNA removal 0
  • complement 0
  • long_read 0
  • atac-seq 0
  • fam 0
  • somatic variants 0
  • aln 0
  • cut up 0
  • proteome 0
  • bracken 0
  • bim 0
  • cool 0
  • mzml 0
  • gatk4spark 0
  • mapper 0
  • repeat expansion 0
  • CRISPR 0
  • combine 0
  • comparisons 0
  • prefetch 0
  • windowmasker 0
  • fcs-gx 0
  • prokka 0
  • bwameth 0
  • guide tree 0
  • amplicon sequences 0
  • kraken 0
  • structural_variants 0
  • chip-seq 0
  • lineage 0
  • wig 0
  • microbes 0
  • pangolin 0
  • covid 0
  • pan-genome 0
  • hi-c 0
  • pairsam 0
  • comparison 0
  • gene expression 0
  • variant_calling 0
  • cellranger 0
  • replace 0
  • mkfastq 0
  • nucleotide 0
  • insert 0
  • C to T 0
  • dump 0
  • das tool 0
  • regions 0
  • roh 0
  • intervals 0
  • mlst 0
  • fingerprint 0
  • organelle 0
  • genomes 0
  • scaffold 0
  • converter 0
  • PCA 0
  • vrhyme 0
  • deeparg 0
  • scores 0
  • das_tool 0
  • graph layout 0
  • shigella 0
  • small genome 0
  • haplogroups 0
  • genetics 0
  • duplicate 0
  • functional analysis 0
  • k-mer frequency 0
  • tnhaplotyper2 0
  • signature 0
  • interactions 0
  • rrna 0
  • de novo assembler 0
  • ancient dna 0
  • switch 0
  • xz 0
  • hla 0
  • reformat 0
  • megan 0
  • regression 0
  • COBS 0
  • hlala 0
  • hla_typing 0
  • hlala_typing 0
  • read-group 0
  • Read depth 0
  • archive 0
  • mapcounter 0
  • rgfa 0
  • zlib 0
  • taxids 0
  • ChIP-seq 0
  • concordance 0
  • variation 0
  • mitochondrion 0
  • contig 0
  • resolve_bioscience 0
  • effect prediction 0
  • snpeff 0
  • GPU-accelerated 0
  • assembly evaluation 0
  • ampgram 0
  • amptransformer 0
  • snpsift 0
  • cancer genomics 0
  • spatial_transcriptomics 0
  • genomad 0
  • runs_of_homozygosity 0
  • profiles 0
  • junctions 0
  • small variants 0
  • gstama 0
  • taxon name 0
  • SimpleAF 0
  • trancriptome 0
  • multiallelic 0
  • FracMinHash sketch 0
  • tama 0
  • image_processing 0
  • nucleotides 0
  • ped 0
  • gene set 0
  • registration 0
  • GC content 0
  • gene set analysis 0
  • proportionality 0
  • differential expression 0
  • phase 0
  • checksum 0
  • leviosam2 0
  • metamaps 0
  • salmon 0
  • barcode 0
  • primer 0
  • soft-clipped clusters 0
  • pharokka 0
  • taxon tables 0
  • otu tables 0
  • varcal 0
  • instability 0
  • pair 0
  • standardisation 0
  • msi 0
  • minhash 0
  • interactive 0
  • krakenuniq 0
  • standardise 0
  • serogroup 0
  • lofreq 0
  • salmonella 0
  • homoploymer 0
  • purge duplications 0
  • library 0
  • bam2fq 0
  • preseq 0
  • collate 0
  • adapter 0
  • function 0
  • retrotransposons 0
  • MSI 0
  • long terminal repeat 0
  • dict 0
  • fixmate 0
  • long terminal retrotransposon 0
  • kma 0
  • import 0
  • mash 0
  • taxonomic profile 0
  • tumor 0
  • maximum likelihood 0
  • polyA_tail 0
  • refine 0
  • svdb 0
  • mudskipper 0
  • reformatting 0
  • iphop 0
  • orf 0
  • vg 0
  • Streptococcus pneumoniae 0
  • bloom filter 0
  • rtgtools 0
  • instrain 0
  • lift 0
  • k-mer index 0
  • nextclade 0
  • transformation 0
  • micro-satellite-scan 0
  • rename 0
  • krakentools 0
  • tree 0
  • variant pruning 0
  • screen 0
  • msisensor-pro 0
  • bustools 0
  • bfiles 0
  • transcriptomic 0
  • parallelized 0
  • standardization 0
  • orthology 0
  • subset 0
  • Duplication purging 0
  • vcflib 0
  • removal 0
  • polish 0
  • immunoprofiling 0
  • join 0
  • repeat_expansions 0
  • duplex 0
  • fetch 0
  • GEO 0
  • frame-shift correction 0
  • long-read sequencing 0
  • metagenomic 0
  • identifier 0
  • sequence analysis 0
  • expansionhunterdenovo 0
  • metadata 0
  • reheader 0
  • tab 0
  • intersection 0
  • windows 0
  • pharmacogenetics 0
  • emboss 0
  • doublets 0
  • eigenstrat 0
  • anndata 0
  • validate 0
  • UMIs 0
  • unaligned 0
  • samplesheet 0
  • smrnaseq 0
  • xenograft 0
  • MCMICRO 0
  • graft 0
  • trim 0
  • allele-specific 0
  • mirdeep2 0
  • RNA sequencing 0
  • realignment 0
  • microbial 0
  • microscopy 0
  • Pharmacogenetics 0
  • deconvolution 0
  • bayesian 0
  • concat 0
  • tbi 0
  • intersect 0
  • normalize 0
  • norm 0
  • merge mate pairs 0
  • reads merging 0
  • short reads 0
  • region 0
  • sizes 0
  • ome-tif 0
  • nanostring 0
  • trgt 0
  • pigz 0
  • find 0
  • split_kmers 0
  • corrupted 0
  • calling 0
  • nacho 0
  • cnv calling 0
  • CNV 0
  • mRNA 0
  • screening 0
  • vdj 0
  • single cells 0
  • estimation 0
  • genome bins 0
  • recombination 0
  • eCLIP 0
  • splice 0
  • parse 0
  • cleaning 0
  • correction 0
  • bases 0
  • heatmap 0
  • format 0
  • eido 0
  • haplotypes 0
  • awk 0
  • blastp 0
  • deseq2 0
  • rna-seq 0
  • blastn 0
  • spatial_omics 0
  • human removal 0
  • random forest 0
  • metagenomes 0
  • gene labels 0
  • structural-variant calling 0
  • hostile 0
  • fasterq-dump 0
  • sra-tools 0
  • settings 0
  • decontamination 0
  • version 0
  • interval list 0
  • scatter 0
  • gatk 0
  • NRPS 0
  • evidence 0
  • MaltExtract 0
  • HOPS 0
  • panelofnormals 0
  • baf 0
  • authentication 0
  • edit distance 0
  • dereplicate 0
  • secondary metabolites 0
  • RiPP 0
  • allele 0
  • demultiplexed reads 0
  • antibiotics 0
  • aggregate 0
  • artic 0
  • simulate 0
  • antismash 0
  • RNA-Seq 0
  • WGS 0
  • joint genotyping 0
  • cgMLST 0
  • samples 0
  • orthologs 0
  • ragtag 0
  • repeats 0
  • filtermutectcalls 0
  • qualty 0
  • gem 0
  • gwas 0
  • hmmscan 0
  • short-read sequencing 0
  • alr 0
  • blat 0
  • yahs 0
  • detecting svs 0
  • Bioinformatics Tools 0
  • confidence 0
  • phylogenies 0
  • geo 0
  • chloroplast 0
  • hmmpress 0
  • patch 0
  • hhsuite 0
  • mapad 0
  • covariance models 0
  • trna 0
  • clr 0
  • missingness 0
  • reference compression 0
  • baftest 0
  • svtk/baftest 0
  • regex 0
  • impute 0
  • scanner 0
  • whamg 0
  • constant 0
  • wham 0
  • reference panel 0
  • unmarkduplicates 0
  • junction 0
  • references 0
  • sccmec 0
  • variantcalling 0
  • c to t 0
  • adna 0
  • dnamodelapply 0
  • workflow_mode 0
  • groupby 0
  • createreadcountpanelofnormals 0
  • taxonomic composition 0
  • denoisereadcounts 0
  • metaspace 0
  • metabolite annotation 0
  • readwriter 0
  • mzML 0
  • snakemake 0
  • data-download 0
  • Immune Deconvolution 0
  • ribosomal RNA 0
  • rRNA 0
  • prepare 0
  • hwe 0
  • catpack 0
  • Computational Immunology 0
  • workflow 0
  • tnscope 0
  • genome annotation 0
  • readproteingroups 0
  • dnascope 0
  • 16S 0
  • proteus 0
  • streptococcus 0
  • spa 0
  • spatype 0
  • mobile genetic elements 0
  • integron 0
  • patterns 0
  • signatures 0
  • doublet 0
  • countsvtypes 0
  • eigenvectors 0
  • hicPCA 0
  • fracminhash sketch 0
  • hash sketch 0
  • sliding 0
  • bgen 0
  • CRISPRi 0
  • pruning 0
  • rdtest2vcf 0
  • downsample 0
  • longest 0
  • isoform 0
  • upd 0
  • transcroder 0
  • cds 0
  • uniparental 0
  • disomy 0
  • snv 0
  • variancepartition 0
  • coding 0
  • sequencing adapters 0
  • downsample bam 0
  • subsample bam 0
  • vcf2db 0
  • gemini 0
  • maf 0
  • eucaryotes 0
  • lua 0
  • dream 0
  • toml 0
  • chromosomal rearrangements 0
  • agat 0
  • drep 0
  • vcfbreakmulti 0
  • pca 0
  • linkage equilibrium 0
  • refflat 0
  • genepred 0
  • bedtobigbed 0
  • ucsc/liftover 0
  • bigbed 0
  • f coefficient 0
  • homozygous genotypes 0
  • heterozygous genotypes 0
  • inbreeding 0
  • umicollapse 0
  • microbial genomics 0
  • bedgraphtobigwig 0
  • scRNA-Seq 0
  • plink2_pca 0
  • bgen file 0
  • covariance model 0
  • dereplication 0
  • files 0
  • vcf file 0
  • genotype dosages 0
  • Mycobacterium tuberculosis 0
  • assembly polishing 0
  • rdtest 0
  • SNV 0
  • remove samples 0
  • extractunbinned 0
  • tandem repeats 0
  • linkbins 0
  • long read 0
  • decompress 0
  • sintax 0
  • vsearch/sort 0
  • vcf2bed 0
  • shuffleBed 0
  • Indel 0
  • trio binning 0
  • host removal 0
  • usearch 0
  • long read alignment 0
  • pangenome-scale 0
  • all versus all 0
  • mashmap 0
  • gtftogenepred 0
  • wavefront 0
  • haploype 0
  • helitron 0
  • polya tail 0
  • fast5 0
  • genome polishing 0
  • network 0
  • bedcov 0
  • uniq 0
  • deduplicate 0
  • paired reads re-pairing 0
  • comp 0
  • md 0
  • VCFtools 0
  • nm 0
  • wget 0
  • uq 0
  • verifybamid 0
  • GFF/GTF 0
  • short 0
  • intron 0
  • DNA contamination estimation 0
  • SINE 0
  • masking 0
  • low-complexity 0
  • plant 0
  • construct 0
  • melon 0
  • graph projection to vcf 0
  • boxcox 0
  • busco 0
  • fix 0
  • tag2tag 0
  • association 0
  • GWAS 0
  • svg 0
  • case/control 0
  • xml 0
  • script 0
  • java 0
  • associations 0
  • rank 0
  • spatial_neighborhoods 0
  • hashing-based deconvolution 0
  • tags 0
  • standard 0
  • impute-info 0
  • functional 0
  • Illumina 0
  • scimap 0
  • Bayesian 0
  • uniques 0
  • invariant 0
  • structural-variants 0
  • omics 0
  • biological activity 0
  • drug categorization 0
  • prior knowledge 0
  • refresh 0
  • clahe 0
  • cell_barcodes 0
  • microRNA 0
  • telseq 0
  • stardist 0
  • variant-calling 0
  • poolseq 0
  • multi-tool 0
  • predict 0
  • search engine 0
  • mass_error 0
  • hardy-weinberg 0
  • hwe statistics 0
  • multiqc 0
  • hwe equilibrium 0
  • haplotag 0
  • reference-independent 0
  • genotype likelihood 0
  • Staging 0
  • collapse 0
  • liftover 0
  • probabilistic realignment 0
  • seqfu 0
  • n50 0
  • cell_type_identification 0
  • cell_phenotyping 0
  • machine_learning 0
  • staging 0
  • tag 0
  • mygene 0
  • vsearch/dereplicate 0
  • coreutils 0
  • transcription factors 0
  • regulatory network 0
  • 10x 0
  • ribosomal 0
  • grabix 0
  • hamming-distance 0
  • bwameme 0
  • bwamem2 0
  • guidetree 0
  • hashing-based deconvoltion 0
  • gnu 0
  • Pacbio 0
  • overlap-based merging 0
  • generic 0
  • AC/NS/AF 0
  • vcflib/vcffixup 0
  • trimfq 0
  • cellsnp 0
  • transposable element 0
  • retrieval 0
  • donor deconvolution 0
  • genotype-based demultiplexing 0
  • MMseqs2 0
  • lexogen 0
  • droplet based single cells 0
  • check 0
  • paired reads merging 0
  • Read report 0
  • orthogroup 0
  • go 0
  • Read trimming 0
  • Read filters 0
  • nanoq 0
  • redundant 0
  • pile up 0
  • extraction 0
  • featuretable 0
  • mass spectrometry 0
  • sage 0
  • nanopore sequencing 0
  • rna velocity 0
  • translation 0
  • cobra 0
  • spot 0
  • circular 0
  • extension 0
  • realign 0
  • quality check 0
  • size 0
  • cram-size 0
  • selector 0
  • grea 0
  • paraphase 0
  • functional enrichment 0
  • homologs 0
  • vsearch/fastqfilter 0
  • malformed 0
  • rad 0
  • tnfilter 0
  • plotting 0
  • scanpy 0
  • array_cgh 0
  • cytosure 0
  • metagenome assembler 0
  • vector 0
  • gprofiler2 0
  • gost 0
  • morphology 0
  • resegment 0
  • relabel 0
  • regtools 0
  • cell segmentation 0
  • nuclear segmentation 0
  • structural variant 0
  • bam2fastx 0
  • import segmentation 0
  • bam2fastq 0
  • immcantation 0
  • airrseq 0
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  • element 0
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  • trimBam 0
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  • post Post-processing 0
  • model 0
  • AMPs 0
  • antimicrobial peptide prediction 0
  • Staphylococcus aureus 0
  • installation 0
  • affy 0
  • reference panels 0
  • admixture 0
  • adapterremoval 0
  • antimicrobial reistance 0
  • contiguate 0
  • doCounts 0
  • HLA 0
  • lifestyle 0
  • read group 0
  • autofluorescence 0
  • cycif 0
  • background 0
  • single-stranded 0
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  • bias 0
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  • http(s) 0
  • unionBedGraphs 0
  • file manipulation 0
  • deletion 0
  • Segmentation 0
  • cutesv 0
  • gct 0
  • cls 0
  • na 0
  • custom 0
  • Cores 0
  • TMA dearray 0
  • paired-end 0
  • UNet 0
  • mcool 0
  • genomic bins 0
  • makebins 0
  • enzyme 0
  • digest 0
  • pcr duplicates 0
  • track 0
  • cooler/balance 0
  • escherichia coli 0
  • circos 0
  • eklipse 0
  • eigenstratdatabasetools 0
  • pep 0
  • schema 0
  • PEP 0
  • depth information 0
  • corrrelation 0
  • structural variation 0
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  • domains 0
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  • antibody capture 0
  • calder2 0
  • cadd 0
  • postprocessing 0
  • tblastn 0
  • subtyping 0
  • Salmonella enterica 0
  • antigen capture 0
  • crispr 0
  • nucleotide composition 0
  • cmseq 0
  • concoct 0
  • partition histograms 0
  • protein coding genes 0
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  • polymorphic sites 0
  • polymorphic 0
  • polymut 0
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  • chromap 0
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  • mitochondrial 0
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copy number profiles of tumour cells.

01234000000

allelefreqs bafs cnvs logrs metrics png purityploidy segments versions

Calculate the sequence-accessible coordinates in chromosomes from the given reference genome, output as a BED file.

0101

bed versions

cnvkit:

CNVkit is a Python library and command-line software toolkit to infer and visualize copy number from high-throughput DNA sequencing data. It is designed for use with hybrid capture, including both whole-exome and custom target panels, and short-read sequencing platforms such as Illumina and Ion Torrent.

Derive off-target (โ€œantitargetโ€) bins from target regions.

01

bed versions

cnvkit:

CNVkit is a Python library and command-line software toolkit to infer and visualize copy number from high-throughput DNA sequencing data. It is designed for use with hybrid capture, including both whole-exome and custom target panels, and short-read sequencing platforms such as Illumina and Ion Torrent.

Copy number variant detection from high-throughput sequencing data

012010101010

bed cnn cnr cns pdf png versions

cnvkit:

CNVkit is a Python library and command-line software toolkit to infer and visualize copy number from high-throughput DNA sequencing data. It is designed for use with hybrid capture, including both whole-exome and custom target panels, and short-read sequencing platforms such as Illumina and Ion Torrent.

Given segmented log2 ratio estimates (.cns), derive each segmentโ€™s absolute integer copy number

012

cns versions

cnvkit:

CNVkit is a Python library and command-line software toolkit to infer and visualize copy number from high-throughput DNA sequencing data. It is designed for use with hybrid capture, including both whole-exome and custom target panels, and short-read sequencing platforms such as Illumina and Ion Torrent.

Convert copy number ratio tables (.cnr files) or segments (.cns) to another format.

01

output versions

cnvkit:

CNVkit is a Python library and command-line software toolkit to infer and visualize copy number from high-throughput DNA sequencing data. It is designed for use with hybrid capture, including both whole-exome and custom target panels, and short-read sequencing platforms such as Illumina and Ion Torrent.

Copy number variant detection from high-throughput sequencing data

012

tsv cnn versions

cnvkit:

CNVkit is a Python library and command-line software toolkit to infer and visualize copy number from high-throughput DNA sequencing data. It is designed for use with hybrid capture, including both whole-exome and custom target panels, and short-read sequencing platforms such as Illumina and Ion Torrent.

Compile a coverage reference from the given files (normal samples).

000

cnn versions

cnvkit:

CNVkit is a Python library and command-line software toolkit to infer and visualize copy number from high-throughput DNA sequencing data. It is designed for use with hybrid capture, including both whole-exome and custom target panels, and short-read sequencing platforms such as Illumina and Ion Torrent.

Transform bait intervals into targets more suitable for CNVkit.

0101

bed versions

cnvkit:

CNVkit is a Python library and command-line software toolkit to infer and visualize copy number from high-throughput DNA sequencing data. It is designed for use with hybrid capture, including both whole-exome and custom target panels, and short-read sequencing platforms such as Illumina and Ion Torrent.

CNVnator is a command line tool for CNV/CNA analysis from depth-of-coverage by mapped reads.

012010101

root tab versions

cnvnator:

Tool for calling copy number variations.

convert2vcf.pl is command line tool to convert CNVnator calls to vcf format.

01

vcf versions

cnvnator:

Tool for calling copy number variations.

Add both Wilcoxon test and Kolmogorov-Smirnov test p-values to each CNV output of FREEC

012

p_value_txt versions

controlfreec/assesssignificance:

Copy number and genotype annotation from whole genome and whole exome sequencing data.

Copy number and genotype annotation from whole genome and whole exome sequencing data

0123456000000000

bedgraph control_cpn sample_cpn gcprofile_cpn BAF CNV info ratio config versions

controlfreec/freec:

Copy number and genotype annotation from whole genome and whole exome sequencing data.

Plot Freec output

01

bed versions

controlfreec:

Copy number and genotype annotation from whole genome and whole exome sequencing data.

Format Freec output to circos input format

01

circos versions

controlfreec:

Copy number and genotype annotation from whole genome and whole exome sequencing data.

Plot Freec output

0123

png_baf png_ratio_log2 png_ratio versions

controlfreec:

Copy number and genotype annotation from whole genome and whole exome sequencing data.

Plot Freec output

012

png_baf png_ratio_log2 png_ratio versions

controlfreec:

Copy number and genotype annotation from whole genome and whole exome sequencing data.

Determines the baseline contig ploidy for germline samples given counts data

0123010

calls model 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.

Converts copy number ratios (and optonally allelic counts) to copy number segments

01

segmented 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.

Postprocesses the output of GermlineCNVCaller and generates VCFs and denoised copy ratios

0123

intervals segments denoised 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.

ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, particularly for use in cell-free DNA. This module generates a panel of normals

000000

rds txt versions

ichorcna:

Estimating tumor fraction in cell-free DNA from ultra-low-pass whole genome sequencing.

ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, particularly for use in cell-free DNA

010000000

rdata seg cna_seg seg_txt corrected_depth ichorcna_params plots genome_plot versions

ichorcna:

Estimating tumor fraction in cell-free DNA from ultra-low-pass whole genome sequencing.

Calculate intervals coverage for each sample. N.B. the tool can not handle staging files with symlinks, stageInMode should be set to 'link'.

0120

txt png loess_qc_txt loess_txt versions

purecn:

Copy number calling and SNV classification using targeted short read sequencing

Generate on and off-target intervals for PureCN from a list of targets

01010

txt bed versions

purecn:

Copy number calling and SNV classification using targeted short read sequencing

Build a normal database for coverage normalization from all the (GC-normalized) normal coverage files. N.B. as reported in https://www.bioconductor.org/packages/devel/bioc/vignettes/PureCN/inst/doc/Quick.html, it is advised to provide a normal panel (VCF format) to precompute mapping bias for faster runtimes.

012300

rds png bias_rds bias_bed low_cov_bed versions

purecn:

Copy number calling and SNV classification using targeted short read sequencing

Run PureCN workflow to normalize, segment and determine purity and ploidy

01200

pdf local_optima_pdf seg genes_csv amplification_pvalues_csv vcf_gz variants_csv loh_csv chr_pdf segmentation_pdf multisample_seg versions

purecn:

Copy number calling and SNV classification using targeted short read sequencing

Sequenza-utils bam2seqz process BAM and Wiggle files to produce a seqz file

01200

seqz versions

sequenzautils:

Sequenza-utils provides 3 main command line programs to transform common NGS file format - such as FASTA, BAM - to input files for the Sequenza R package. The program - bam2seqz - process a paired set of BAM/pileup files (tumour and matching normal), and GC-content genome-wide information, to extract the common positions with A and B alleles frequencies.

Sequenza-utils gc_wiggle computes the GC percentage across the sequences, and returns a file in the UCSC wiggle format, given a fasta file and a window size.

01

wig versions

sequenzautils:

Sequenza-utils provides 3 main command line programs to transform common NGS file format - such as FASTA, BAM - to input files for the Sequenza R package. The program -gc_wiggle- takes fasta file as an input, computes GC percentage across the sequences and returns a file in the UCSC wiggle format.

tool to call the copy number of full-length SMN1, full-length SMN2, as well as SMN2ฮ”7โ€“8 (SMN2 with a deletion of Exon7-8) from a whole-genome sequencing (WGS) BAM file.

012

smncopynumber run_metrics versions

Convert and filter aligned reads to .npz

0120101

npz versions

wisecondorx:

WIthin-SamplE COpy Number aberration DetectOR, including sex chromosomes

Returns the gender of a .npz resulting from convert, based on a Gaussian mixture model trained during the newref phase

0101

gender versions

wisecondorx:

WIthin-SamplE COpy Number aberration DetectOR, including sex chromosomes

Create a new reference using healthy reference samples

01

npz versions

wisecondorx:

WIthin-SamplE COpy Number aberration DetectOR, including sex chromosomes

Find copy number aberrations

010101

aberrations_bed bins_bed segments_bed chr_statistics chr_plots genome_plot versions

wisecondorx:

WIthin-SamplE COpy Number aberration DetectOR, including sex chromosomes

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