Explore Workflows

# Set Operations for filtered gene lists This workflow takes as input multiple filtered genelists samples and performs the user-selected set operation on them. There is one input for list A from which \"scores\" will be taken (these are fold change values from deseq or diffbind) and used in the output set list. The second genelist input is for 1+ genelists, that will be aggregated and used for intersection and union directly, and be applied against list A for the relative complement operation. The output is a single filtered gene list in the same format as the input files (headerless BED file with [chrom start end name score strand]). The returned score value (column 5) is always derived from file A.

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

Path: workflows/genelists-sets.cwl

Branch/Commit ID: cc6fa135d04737fdde3b4414d6e214cf8c812f6e

https://github.com/nigyta/bact_genome.git

Path: cwl/workflow/platanusB-default.cwl

Branch/Commit ID: d0d36f70eb62164d57c1ba27a6b63bee7d41e370

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: 64f7fe4438898218fd83133efa25251078f5b27e

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

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

Branch/Commit ID: 26870e38cec81af880cd3e4789ae6cee8fc27020

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

Path: task_types/tt_univec_wnode.cwl

Branch/Commit ID: 861d9baa067af98d794ba0ed4e43aa42e37d8a24

DiffBind Multi-factor Analysis DiffBind processes ChIP-Seq data enriched for genomic loci where specific protein/DNA binding occurs, including peak sets identified by ChIP-Seq peak callers and aligned sequence read datasets. It is designed to work with multiple peak sets simultaneously, representing different ChIP experiments (antibodies, transcription factor and/or histone marks, experimental conditions, replicates) as well as managing the results of multiple peak callers. For more information please refer to: ------------------------------------- Ross-Innes CS, Stark R, Teschendorff AE, Holmes KA, Ali HR, Dunning MJ, Brown GD, Gojis O, Ellis IO, Green AR, Ali S, Chin S, Palmieri C, Caldas C, Carroll JS (2012). “Differential oestrogen receptor binding is associated with clinical outcome in breast cancer.” Nature, 481, -4.

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

Path: workflows/diffbind-multi-factor.cwl

Branch/Commit ID: 22880e0f41d0420a17d643e8a6e8ee18165bbfbf

Cell Ranger Count Gene Expression Quantifies gene expression from a single-cell RNA-Seq library.

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

Path: workflows/single-cell-preprocess-cellranger.cwl

Branch/Commit ID: 22880e0f41d0420a17d643e8a6e8ee18165bbfbf

Single-cell Pseudobulk Differential Expression Analysis Between Datasets Identifies differentially expressed genes between groups of cells coerced to pseudobulk datasets.

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

Path: workflows/sc-rna-de-pseudobulk.cwl

Branch/Commit ID: 12e5256de1b680c551c87fd5db6f3bc65428af67

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: 64f7fe4438898218fd83133efa25251078f5b27e

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

Path: tests/wf/cache_test_workflow.cwl

Branch/Commit ID: d5f7fa162611243f0c66dd3e933c16a4964a09ca