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Graph Name Retrieved From View
workflow graph find_hotspots_in_normals.cwl

Workflow to find hotspot VAFs from duplex (for Tumor sample) and unfiltered (for Normal sample) pileups. These inputs are all required to be sorted in the same order: sample_ids patient_ids sample_classes unfiltered_pileups duplex_pileups

https://github.com/andurill/access-pipeline.git

Path: workflows/subworkflows/find_hotspots_in_normals.cwl

Branch/Commit ID: 3441040dfaecba58150c13a95a6a93657b00778a
workflow graph conflict-wf.cwl#collision

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

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

Branch/Commit ID: 22490926651174c6cbe01c76c2ded3c9e8d0ee6f

Packed ID: collision
workflow graph run_test.cwl

https://github.com/rosafilgueira/dare_seismo.git

Path: specfem3d/specfem3d_test_input_cwl/run_test.cwl

Branch/Commit ID: 1bec173f62a5ba91c938a6f00f49c07af94288c1
workflow graph stdout-wf_v1_2.cwl

https://github.com/common-workflow-language/cwl-utils.git

Path: testdata/stdout-wf_v1_2.cwl

Branch/Commit ID: 124a08ce3389eb49066c34a4163cbbed210a0355
workflow graph Kraken2 Metagenomic pipeline paired-end

This workflow taxonomically classifies paired-end sequencing reads in FASTQ format, that have been optionally adapter trimmed with trimgalore, using Kraken2 and a user-selected pre-built database from a list of [genomic index files](https://benlangmead.github.io/aws-indexes/k2). ### __Inputs__ Kraken2 database for taxonomic classification: - [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) Read 1 file: - FASTA/Q input R1 from a paired end library Read 2 file: - FASTA/Q input R2 from a paired end library Number of threads for steps that support multithreading: - Number of threads for steps that support multithreading - default set to `4` Advanced Inputs Tab (Optional): - Number of bases to clip from the 3p end - Number of bases to clip from the 5p end ### __Outputs__ - k2db, an upstream database used by kraken2 classifier ### __Data Analysis Steps__ 1. Trimming the adapters with TrimGalore. - This step is particularly important when the reads are long and the fragments are short - resulting in sequencing adapters at the ends of reads. If adapter is not removed the read will not map. TrimGalore can recognize standard adapters, such as Illumina or Nextera/Tn5 adapters. 2. Generate quality control statistics of trimmed, unmapped sequence data 3. (Optional) Clipping of 5' and/or 3' end by the specified number of bases. 4. Mapping reads to primary genome index with Bowtie. ### __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-classify-pe.cwl

Branch/Commit ID: 12e5256de1b680c551c87fd5db6f3bc65428af67
workflow graph io-int-wf.cwl

https://github.com/common-workflow-language/cwl-v1.2.git

Path: tests/io-int-wf.cwl

Branch/Commit ID: a5073143db4155e05df8d2e7eb59d9e62acd65a5
workflow graph sequence (bam or fastqs) to trimmed fastqs and HISAT alignments

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/sequence_to_trimmed_fastq_and_hisat_alignments.cwl

Branch/Commit ID: 0d2f354af9192a56af258a7d2426c7c160f4ec1a
workflow graph adapter for sequence_align_and_tag

Some workflow engines won't stage files in our nested structure, so parse it out here

 https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/sequence_align_and_tag_adapter.cwl

Branch/Commit ID: 5fda2d9eb52a363bd51011b3851c2afb86318c0c
workflow graph Exome QC workflow

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/qc_exome_no_verify_bam.cwl

Branch/Commit ID: 5fda2d9eb52a363bd51011b3851c2afb86318c0c
workflow graph Alignment without BQSR

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/sequence_to_bqsr_nonhuman.cwl

Branch/Commit ID: 5fda2d9eb52a363bd51011b3851c2afb86318c0c