Explore Workflows

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

Path: cwltool/schemas/v1.0/v1.0/step-valuefrom-wf.cwl

Branch/Commit ID: 5ae5798f1c0c8d2178986b77cfd74edff510877a

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

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

Path: definitions/pipelines/somatic_exome_cle_gathered.cwl

Branch/Commit ID: bfcb5ffbea3d00a38cc03595d41e53ea976d599d

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

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

Branch/Commit ID: e8b3565a008d95859fc44227987a54e6a53a8c29

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

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

Branch/Commit ID: 1eb6bfe3c77aebaf69453a669d21ae7a5a78056f

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

Path: protein_alignment/wf_compart_filter_prosplign.cwl

Branch/Commit ID: 8af4e2aabf43d5e3c7162efae4ad4649df5601e2

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

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

Path: task_types/tt_taxonomy_check_16S.cwl

Branch/Commit ID: c28cfb9882dedd3c522160f933cff1050ae24100

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

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

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

Path: workflows/manorm2.cwl

Branch/Commit ID: 261c0232a7a40880f2480b811ed2d7e89c463869