Explore Workflows

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Graph Name Retrieved From View
workflow graph Cellranger reanalyze - reruns secondary analysis performed on the feature-barcode matrix

Devel version of Single-Cell Cell Ranger Reanalyze ================================================== Workflow calls \"cellranger aggr\" command to rerun secondary analysis performed on the feature-barcode matrix (dimensionality reduction, clustering and visualization) using different parameter settings. As an input we use filtered feature-barcode matrices in HDF5 format from cellranger count or aggr experiments. Note, we don't pass aggregation_metadata from the upstream cellranger aggr step. Need to address this issue when needed.

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

Path: workflows/cellranger-reanalyze.cwl

Branch/Commit ID: a839eb6390974089e1a558c49fc07b4c66c50767
workflow graph pileups_workflow.cwl

https://github.com/ReddyLab/bird-workflow.git

Path: 01_mpileups/pileups_workflow.cwl

Branch/Commit ID: 5e08b9b8a0323a1f4740a65bdb356e9b75074093
workflow graph Trim Galore RNA-Seq pipeline paired-end strand specific

Modified original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for a **pair-end** experiment. A corresponded input [FASTQ](http://maq.sourceforge.net/fastq.shtml) file has to be provided. Current workflow should be used only with the single-end RNA-Seq data. It performs the following steps: 1. Trim adapters from input FASTQ files 2. Use STAR to align reads from input FASTQ files according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 3. Use fastx_quality_stats to analyze input FASTQ files and generate quality statistics files 4. Use 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 files 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/trim-rnaseq-pe-dutp.cwl

Branch/Commit ID: a839eb6390974089e1a558c49fc07b4c66c50767
workflow graph Subworkflow to allow calling cnvkit with cram instead of bam files

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

Path: definitions/subworkflows/cram_to_cnvkit.cwl

Branch/Commit ID: f77a920bcc73f6cfdb091eed75a149d02cd8a263
workflow graph allele-alignreads-se-pe.cwl

Workflow maps FASTQ files from `fastq_files` input into reference genome `reference_star_indices_folder` and insilico generated `insilico_star_indices_folder` genome (concatenated genome for both `strain1` and `strain2` strains). For both genomes STAR is run with `outFilterMultimapNmax` parameter set to 1 to discard all of the multimapped reads. For insilico genome SAM file is generated. Then it's splitted into two SAM files based on strain names and then sorted by coordinates into the BAM format. For reference genome output BAM file from STAR slignment is also coordinate sorted.

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

Path: subworkflows/allele-alignreads-se-pe.cwl

Branch/Commit ID: 9a2c389364674221fab3f0f6afdda799e6aa3247
workflow graph bact_get_kmer_reference

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

Path: task_types/tt_bact_get_kmer_reference.cwl

Branch/Commit ID: ae781871782805632f8947c1b11f65507c80cd43
workflow graph mutect parallel workflow

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

Path: definitions/subworkflows/mutect.cwl

Branch/Commit ID: 295e7b7f51727c0f2d6cc86ce817449b2e8dba3c
workflow graph wgs alignment with qc

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

Path: definitions/pipelines/wgs_alignment.cwl

Branch/Commit ID: 1560e7817fdb71d58aca7f98aba68809d840ade1
workflow graph Motif Finding with HOMER with target and background regions from peaks

Motif Finding with HOMER with target and background regions from peaks --------------------------------------------------- HOMER contains a novel motif discovery algorithm that was designed for regulatory element analysis in genomics applications (DNA only, no protein). It is a differential motif discovery algorithm, which means that it takes two sets of sequences and tries to identify the regulatory elements that are specifically enriched in on set relative to the other. It uses ZOOPS scoring (zero or one occurrence per sequence) coupled with the hypergeometric enrichment calculations (or binomial) to determine motif enrichment. HOMER also tries its best to account for sequenced bias in the dataset. It was designed with ChIP-Seq and promoter analysis in mind, but can be applied to pretty much any nucleic acids motif finding problem. For more information please refer to: ------------------------------------- [Official documentation](http://homer.ucsd.edu/homer/motif/)

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

Path: workflows/homer-motif-analysis-peak.cwl

Branch/Commit ID: 1131f82a53315cca217a6c84b3bd272aa62e4bca
workflow graph mutect panel-of-normals workflow

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

Path: definitions/pipelines/panel_of_normals.cwl

Branch/Commit ID: 1560e7817fdb71d58aca7f98aba68809d840ade1