Explore Workflows

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

Path: definitions/subworkflows/bam_to_bqsr_no_dup_marking.cwl

Branch/Commit ID: a3e26136043c03192c38c335316d2d36e3e67478

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

Path: definitions/subworkflows/germline_detect_variants.cwl

Branch/Commit ID: 051074fce4afd9732ef34db9dd43d3a1d8e979d6

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

Path: definitions/subworkflows/bisulfite_qc.cwl

Branch/Commit ID: 051074fce4afd9732ef34db9dd43d3a1d8e979d6

Slightly changed original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for **strand specific single-read** experiment. An additional steps were added to map data to mitochondrial chromosome only and then merge the output. Experiment files in [FASTQ](http://maq.sourceforge.net/fastq.shtml) format either compressed or not can be used. Current workflow should be used only with single-read strand specific RNA-Seq data. It performs the following steps: 1. `STAR` to align reads from input FASTQ file according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 2. `fastx_quality_stats` to analyze input FASTQ file and generate quality statistics file 3. `samtools sort` to generate coordinate sorted BAM(+BAI) file pair from the unsorted BAM file obtained on the step 1 (after running STAR) 5. Generate BigWig file on the base of sorted BAM file 6. Map input FASTQ file to predefined rRNA reference indices using Bowtie to define the level of rRNA contamination; export resulted statistics to file 7. Calculate isoform expression level for the sorted BAM file and GTF/TAB annotation file using `GEEP` reads-counting utility; export results to file

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

Path: workflows/rnaseq-se-dutp-mitochondrial.cwl

Branch/Commit ID: 3fc68366adb179927af5528c27b153abaf94494d

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

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

Branch/Commit ID: 875b928ce50a3202f5954843b79ea86683c160fa

Devel version of AltAnalyze Iterative Clustering and Guide-gene Selection =========================================================================

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

Path: workflows/altanalyze-icgs.cwl

Branch/Commit ID: a8eaf61c809d76f55780b14f2febeb363cf6373f

https://github.com/common-workflow-language/cwl-v1.1.git

Path: tests/iwdr_with_nested_dirs.cwl

Branch/Commit ID: 664835e83eb5e57eee18a04ce7b05fb9d70d77b7

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

Path: task_types/tt_blastp_wnode_naming.cwl

Branch/Commit ID: 4a44218a713aecc488359be275409414ae8c1434

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: ebbf23764ede324cabc064bd50647c1f643726fa

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

Path: cwltool/schemas/v1.0/v1.0/count-lines4-wf.cwl

Branch/Commit ID: 7c7615c44b80f8e76e659433f8c7875603ae0b25