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Graph Name Retrieved From View
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 - compressed_k2db_tar, compressed and tarred kraken2 database directory file for download and use outside of scidap ### __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: b4d578c2ba4713a5a22163d9f8c7105acda1f22e
workflow graph tt_hmmsearch_wnode.cwl

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

Path: task_types/tt_hmmsearch_wnode.cwl

Branch/Commit ID: 1e16653514fd5629a704516eb447043c9fd0a53b
workflow graph Run genomic CMsearch

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

Path: bacterial_noncoding/wf_gcmsearch.cwl

Branch/Commit ID: 1e16653514fd5629a704516eb447043c9fd0a53b
workflow graph scatter2.cwl

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

Path: tests/wf/scatter2.cwl

Branch/Commit ID: a67c898958f6affc8cb9de05fe87c9228a4fc63e
workflow graph 811-12.cwl

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

Path: tests/wf/811-12.cwl

Branch/Commit ID: a67c898958f6affc8cb9de05fe87c9228a4fc63e
workflow graph scatterfail.cwl

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

Path: tests/wf/scatterfail.cwl

Branch/Commit ID: a67c898958f6affc8cb9de05fe87c9228a4fc63e
workflow graph Bacterial Annotation, pass 4, blastp-based functional annotation (second pass)

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

Path: bacterial_annot/wf_bacterial_annot_pass4.cwl

Branch/Commit ID: 1e16653514fd5629a704516eb447043c9fd0a53b
workflow graph paramref_arguments_self.cwl

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

Path: tests/wf/paramref_arguments_self.cwl

Branch/Commit ID: a67c898958f6affc8cb9de05fe87c9228a4fc63e
workflow graph SoupX (workflow) - an R package for the estimation and removal of cell free mRNA contamination

Wrapped in a workflow SoupX tool for easy access to Cell Ranger pipeline compressed outputs.

https://github.com/Barski-lab/workflows.git

Path: tools/soupx-subworkflow.cwl

Branch/Commit ID: 9a03dbe8829ca649814d9c8bd11fe3a673750a95
workflow graph heatmap-prepare.cwl

Workflow runs homer-make-tag-directory.cwl tool using scatter for the following inputs - bam_file - fragment_size - total_reads `dotproduct` is used as a `scatterMethod`, so one element will be taken from each array to construct each job: 1) bam_file[0] fragment_size[0] total_reads[0] 2) bam_file[1] fragment_size[1] total_reads[1] ... N) bam_file[N] fragment_size[N] total_reads[N] `bam_file`, `fragment_size` and `total_reads` arrays should have the identical order.

https://github.com/Barski-lab/workflows.git

Path: tools/heatmap-prepare.cwl

Branch/Commit ID: 9a03dbe8829ca649814d9c8bd11fe3a673750a95