Explore Workflows

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

Path: definitions/subworkflows/filter_sv_vcf.cwl

Branch/Commit ID: d2c2f2eb846ae2e9cdcab46e3bb88e42126cb3f5

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

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

Branch/Commit ID: 4c905b830371eee45188a53510ba0ee9113fd4c8

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

Path: cwltool/schemas/v1.0/v1.0/echo-wf-default.cwl

Branch/Commit ID: 665141f319e6b23bd9924b14844f2e979f141944

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: a1f6ca50fcb0881781b3ba0306dd61ebf555eaba

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

Path: task_types/tt_format_rrnas_from_seq_entry.cwl

Branch/Commit ID: cec32f5b60c1d048257e3c3daed6912d5d2a054e

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

Path: definitions/subworkflows/align.cwl

Branch/Commit ID: 051074fce4afd9732ef34db9dd43d3a1d8e979d6

This workflow produces calibration inputs to simulation model: - atmospheric model - extinction hypercube - telescopes' cameras configurations - telescopes' PSFs - optical throughput

https://gitlab.cta-observatory.org/cta-computing/dpps/dpps-workflows.git

Path: workflows/calibpipe/uc-cp-001.cwl

Branch/Commit ID: 76f7c25c0472da23b7e0bfe9f2c18ab6bc369c9d

This workflow takes in appropriate trimming params and demultiplexed reads, and performs the following steps in order: trimx1, trimx2, fastq-sort, filter repeat elements, fastq-sort, genomic mapping, sort alignment, index alignment, namesort, PCR dedup, sort alignment, index alignment

https://github.com/YeoLab/eclip.git

Path: cwl/wf_trim_and_map_se_nostats.cwl

Branch/Commit ID: c0fffc4979a92371dc0667a03e3d957bf7f77600

https://github.com/arvados/arvados-tutorial.git

Path: WGS-processing/cwl/helper/report-wf.cwl

Branch/Commit ID: 2691061efa8341166ad6518688e5e6c0fb9a8fbf

https://github.com/pitagora-network/pitagora-cwl.git

Path: workflows/hisat2-cufflinks/single_end/hisat2-cufflinks_wf_se.cwl

Branch/Commit ID: 4e84905f265e1db212c406d34ae4db2bf565e856