Explore Workflows

View already parsed workflows here or click here to add your own

Graph	Name	Retrieved From	View
	Cell Ranger Multi Gene Expression and V(D)J Repertoire Profiling Cell Ranger Multi Gene Expression and V(D)J Repertoire Profiling Quantifies gene expression and performs profiling of V(D)J repertoire from a single GEM well	https://github.com/datirium/workflows.git Path: workflows/cellranger-multi.cwl Branch/Commit ID: 22880e0f41d0420a17d643e8a6e8ee18165bbfbf
	default-wf5.cwl	https://github.com/common-workflow-language/cwltool.git Path: tests/wf/default-wf5.cwl Branch/Commit ID: d5f7fa162611243f0c66dd3e933c16a4964a09ca
	QuantSeq 3' FWD, FWD-UMI or REV for single-read mRNA-Seq data ### Devel version of QuantSeq 3' FWD, FWD-UMI or REV for single-read mRNA-Seq data	https://github.com/datirium/workflows.git Path: workflows/trim-quantseq-mrnaseq-se-strand-specific.cwl Branch/Commit ID: c6bfa0de917efb536dd385624fc7702e6748e61d
	Filter differentially bound sites for heatmap analysis Filter DiffBind results for deepTools heatmap analysis ====================================================== Filter differentially bound sites from DiffBind analysis to be used with deepTools heatmap analysis	https://github.com/datirium/workflows.git Path: workflows/filter-diffbind-for-heatmap.cwl Branch/Commit ID: cc6fa135d04737fdde3b4414d6e214cf8c812f6e
	RNA-Seq pipeline paired-end stranded mitochondrial 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 pair-end 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 the pair-end 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-pe-dutp-mitochondrial.cwl Branch/Commit ID: 9ee330737f4603e4e959ffe786fbb2046db70a00
	Cell Ranger Aggregate Cell Ranger Aggregate =====================	https://github.com/datirium/workflows.git Path: workflows/cellranger-aggr.cwl Branch/Commit ID: 00ea05e22788029370898fd4c17798b11edf0e57
	autosubmit.cwl An example workflow created using Autosubmit's basic a000 workflow as reference. The `platform.yml` is ignored as it contains only information about platforms (e.g. it could be given to a tool like Troika as-is). `expdef.yml` and `autosubmit.yml` basically provide CWL inputs. `jobs.yml` contains the steps of the CWL workflow, with their dependencies. In CWL dependencies are specified via inputs and outputs. When task A outputs a value X, and task B has an input of type A/X, then the dependency A -> B is created in CWl. This is different than Autosubmit, and needs some care to guarantee the correct order in the workflow graph of start dates, members, chunks, etc.	https://github.com/kinow/kinoshita.eti.br.git Path: notes/autosubmit/autosubmit.cwl Branch/Commit ID: 79725036c608a9cfaeb97465061d66fcc4ccb8a6
	SoupX (workflow) - an R package for the estimation and removal of cell free mRNA contamination Wrapped in a workflow SoupX tool for easy access to Cell Ranger pipeline compressed outputs.	https://github.com/datirium/workflows.git Path: tools/soupx-subworkflow.cwl Branch/Commit ID: d76110e0bfc40c874f82e37cef6451d74df4f908
	Single-Cell Label Integration Analysis Single-Cell Label Integration Analysis Harmonizes conflicting annotations in single-cell genomics studies.	https://github.com/datirium/workflows.git Path: workflows/sc-triangulate.cwl Branch/Commit ID: 57863b6131d8262c5ce864adaf8e4038401e71a2
	MAnorm PE - quantitative comparison of ChIP-Seq paired-end data What is MAnorm? -------------- MAnorm is a robust model for quantitative comparison of ChIP-Seq data sets of TFs (transcription factors) or epigenetic modifications and you can use it for: * Normalization of two ChIP-seq samples * Quantitative comparison (differential analysis) of two ChIP-seq samples * Evaluating the overlap enrichment of the protein binding sites(peaks) * Elucidating underlying mechanisms of cell-type specific gene regulation How MAnorm works? ---------------- MAnorm uses common peaks of two samples as a reference to build the rescaling model for normalization, which is based on the empirical assumption that if a chromatin-associated protein has a substantial number of peaks shared in two conditions, the binding at these common regions will tend to be determined by similar mechanisms, and thus should exhibit similar global binding intensities across samples. The observed differences on common peaks are presumed to reflect the scaling relationship of ChIP-Seq signals between two samples, which can be applied to all peaks. What do the inputs mean? ---------------- ### General Experiment short name/Alias * short name for you experiment to identify among the others ChIP-Seq PE sample 1 * previously analyzed ChIP-Seq paired-end experiment to be used as Sample 1 ChIP-Seq PE sample 2 * previously analyzed ChIP-Seq paired-end experiment to be used as Sample 2 Genome * Reference genome to be used for gene assigning ### Advanced Reads shift size for sample 1 * This value is used to shift reads towards 3' direction to determine the precise binding site. Set as half of the fragment length. Default 100 Reads shift size for sample 2 * This value is used to shift reads towards 5' direction to determine the precise binding site. Set as half of the fragment length. Default 100 M-value (log2-ratio) cutoff * Absolute M-value (log2-ratio) cutoff to define biased (differential binding) peaks. Default: 1.0 P-value cutoff * P-value cutoff to define biased peaks. Default: 0.01 Window size * Window size to count reads and calculate read densities. 2000 is recommended for sharp histone marks like H3K4me3 and H3K27ac, and 1000 for TFs or DNase-seq. Default: 2000	https://github.com/datirium/workflows.git Path: workflows/manorm-pe.cwl Branch/Commit ID: 57863b6131d8262c5ce864adaf8e4038401e71a2