Explore Workflows

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Graph Name Retrieved From View
workflow graph Cell Ranger Multi Gene Expression and V(D)J Repertoire Profiling

Cell Ranger Multi Gene Expression and V(D)J Repertoire Profiling Quantifies gene expression and performs profiling of V(D)J repertoire from a single GEM well

 https://github.com/datirium/workflows.git

Path: workflows/cellranger-multi.cwl

Branch/Commit ID: 7030da528559c7106d156284e50ff0ecedab0c4e
workflow graph gathered exome alignment and somatic variant detection for cle purpose

https://github.com/apaul7/cancer-genomics-workflow.git

Path: definitions/pipelines/somatic_exome_cle_gathered.cwl

Branch/Commit ID: bfcb5ffbea3d00a38cc03595d41e53ea976d599d
workflow graph count-lines8-wf.cwl

https://github.com/common-workflow-language/cwltool.git

Path: cwltool/schemas/v1.0/v1.0/count-lines8-wf.cwl

Branch/Commit ID: e8b3565a008d95859fc44227987a54e6a53a8c29
workflow graph count-lines5-wf.cwl

https://github.com/common-workflow-language/cwltool.git

Path: cwltool/schemas/v1.0/v1.0/count-lines5-wf.cwl

Branch/Commit ID: 1eb6bfe3c77aebaf69453a669d21ae7a5a78056f
workflow graph Filter Protein Seeds; Find ProSplign Alignments

https://github.com/ncbi/pgap.git

Path: protein_alignment/wf_compart_filter_prosplign.cwl

Branch/Commit ID: 8af4e2aabf43d5e3c7162efae4ad4649df5601e2
workflow graph conflict-wf.cwl#collision

https://github.com/common-workflow-language/cwltool.git

Path: cwltool/schemas/v1.0/v1.0/conflict-wf.cwl

Branch/Commit ID: bbe20f54deea92d9c9cd38cb1f23c4423133d3de

Packed ID: collision
workflow graph taxonomy_check_16S

https://github.com/ncbi/pgap.git

Path: task_types/tt_taxonomy_check_16S.cwl

Branch/Commit ID: c28cfb9882dedd3c522160f933cff1050ae24100
workflow graph Kraken2 Database installation pipeline

This workflow downloads the user-selected pre-built kraken2 database from: https://benlangmead.github.io/aws-indexes/k2 ### __Inputs__ Select a pre-built Kraken2 database to download and use for metagenomic classification: - Available options comprised of various combinations of RefSeq reference genome sets: - [Viral (0.5 GB)](https://genome-idx.s3.amazonaws.com/kraken/k2_viral_20221209.tar.gz), all refseq viral genomes - [MinusB (8.7 GB)](https://genome-idx.s3.amazonaws.com/kraken/k2_minusb_20221209.tar.gz), standard minus bacteria (archaea, viral, plasmid, human1, UniVec_Core) - [PlusPFP-16 (15.0 GB)](https://genome-idx.s3.amazonaws.com/kraken/k2_pluspfp_16gb_20221209.tar.gz), standard (archaea, bacteria, viral, plasmid, human1, UniVec_Core) + (protozoa, fungi & plant) capped at 16 GB (shrunk via random kmer downselect) - [EuPathDB46 (34.1 GB)](https://genome-idx.s3.amazonaws.com/kraken/k2_eupathdb48_20201113.tar.gz), eukaryotic pathogen genomes with contaminants removed (https://veupathdb.org/veupathdb/app) - [16S_gg_13_5 (73 MB)](https://genome-idx.s3.amazonaws.com/kraken/16S_Greengenes13.5_20200326.tgz), Greengenes 16S rRNA database ([release 13.5](https://greengenes.secondgenome.com/?prefix=downloads/greengenes_database/gg_13_5/), 20200326)\n - [16S_silva_138 (112 MB)](https://genome-idx.s3.amazonaws.com/kraken/16S_Silva138_20200326.tgz), SILVA 16S rRNA database ([release 138.1](https://www.arb-silva.de/documentation/release-1381/), 20200827) ### __Outputs__ - k2db, an upstream database used by kraken2 classification tool ### __Data Analysis Steps__ 1. download selected pre-built kraken2 database. 2. make available as upstream source for kraken2 metagenomic taxonomic classification. ### __References__ - Wood, D.E., Lu, J. & Langmead, B. Improved metagenomic analysis with Kraken 2. Genome Biol 20, 257 (2019). https://doi.org/10.1186/s13059-019-1891-0

https://github.com/datirium/workflows.git

Path: workflows/kraken2-databases.cwl

Branch/Commit ID: 261c0232a7a40880f2480b811ed2d7e89c463869
workflow graph MAnorm2 for Normalizing and Comparing ChIP-Seq/ATAC-Seq Samples

MAnorm2 for Normalizing and Comparing ChIP-Seq/ATAC-Seq Samples

 https://github.com/datirium/workflows.git

Path: workflows/manorm2.cwl

Branch/Commit ID: 261c0232a7a40880f2480b811ed2d7e89c463869
workflow graph Trim Galore RNA-Seq pipeline single-read strand specific

Note: should be updated The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for a **single-end** experiment. A corresponded input [FASTQ](http://maq.sourceforge.net/fastq.shtml) file has to be provided. Current workflow should be used only with the single-end RNA-Seq data. It performs the following steps: 1. Trim adapters from input FASTQ file 2. Use STAR to align reads from input FASTQ file according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 3. Use fastx_quality_stats to analyze input FASTQ file and generate quality statistics file 4. Use samtools sort to generate coordinate sorted BAM(+BAI) file pair from the unsorted BAM file obtained on the step 1 (after running STAR) 5. Generate BigWig file on the base of sorted BAM file 6. Map input FASTQ file to predefined rRNA reference indices using Bowtie to define the level of rRNA contamination; export resulted statistics to file 7. Calculate isoform expression level for the sorted BAM file and GTF/TAB annotation file using GEEP reads-counting utility; export results to file

https://github.com/datirium/workflows.git

Path: workflows/trim-rnaseq-se-dutp.cwl

Branch/Commit ID: 9ee330737f4603e4e959ffe786fbb2046db70a00