Explore Workflows

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Graph Name Retrieved From View
workflow graph kmer_top_n_extract

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

Path: task_types/tt_kmer_top_n_extract.cwl

Branch/Commit ID: 9362082213e20315f76f6f5c235cac3aae565747
workflow graph Subworkflow to allow calling different SV callers which require bam files as inputs

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

Path: definitions/subworkflows/single_sample_sv_callers.cwl

Branch/Commit ID: f9600f9959acdc30259ba7e64de61104c9b01f0b
workflow graph tt_univec_wnode.cwl

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

Path: task_types/tt_univec_wnode.cwl

Branch/Commit ID: 9362082213e20315f76f6f5c235cac3aae565747
workflow graph Non-Coding Bacterial Genes

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

Path: bacterial_noncoding/wf_bacterial_noncoding.cwl

Branch/Commit ID: 609aead9804a8f31fa9b3dbc7e52105aec487f31
workflow graph zip_and_index_vcf.cwl

This is a very simple workflow of two steps. It will zip an input VCF file and then index it. The zipped file and the index file will be in the workflow output.

https://github.com/baminou/OxoG-Dockstore-Tools.git

Path: zip_and_index_vcf.cwl

Branch/Commit ID: 95da3d32ee8787361333b2eea09afb8f9c3392a9
workflow graph tt_univec_wnode.cwl

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

Path: task_types/tt_univec_wnode.cwl

Branch/Commit ID: 609aead9804a8f31fa9b3dbc7e52105aec487f31
workflow graph concat.cwl

https://github.com/mskcc/pluto-cwl.git

Path: cwl/concat.cwl

Branch/Commit ID: 7eb2b0a4d37018142233d770595ac2e00376dab4
workflow graph blastp_wnode_naming

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

Path: task_types/tt_blastp_wnode_naming.cwl

Branch/Commit ID: 9362082213e20315f76f6f5c235cac3aae565747
workflow graph Bismark Methylation - pipeline for BS-Seq data analysis

Sequence reads are first cleaned from adapters and transformed into fully bisulfite-converted forward (C->T) and reverse read (G->A conversion of the forward strand) versions, before they are aligned to similarly converted versions of the genome (also C->T and G->A converted). Sequence reads that produce a unique best alignment from the four alignment processes against the bisulfite genomes (which are running in parallel) are then compared to the normal genomic sequence and the methylation state of all cytosine positions in the read is inferred. A read is considered to align uniquely if an alignment has a unique best alignment score (as reported by the AS:i field). If a read produces several alignments with the same number of mismatches or with the same alignment score (AS:i field), a read (or a read-pair) is discarded altogether. On the next step we extract the methylation call for every single C analysed. The position of every single C will be written out to a new output file, depending on its context (CpG, CHG or CHH), whereby methylated Cs will be labelled as forward reads (+), non-methylated Cs as reverse reads (-). The output of the methylation extractor is then transformed into a bedGraph and coverage file. The bedGraph counts output is then used to generate a genome-wide cytosine report which reports the number on every single CpG (optionally every single cytosine) in the genome, irrespective of whether it was covered by any reads or not. As this type of report is informative for cytosines on both strands the output may be fairly large (~46mn CpG positions or >1.2bn total cytosine positions in the human genome).

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

Path: workflows/bismark-methylation-se.cwl

Branch/Commit ID: 8049a781ac4aae579fbd3036fa0bf654532f15be
workflow graph umi molecular alignment workflow

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

Path: definitions/subworkflows/molecular_alignment.cwl

Branch/Commit ID: 1750cd5cc653f058f521b6195e3bec1e7df1a086