Explore Workflows
View already parsed workflows here or click here to add your own
| Graph | Name | Retrieved From | View |
|---|---|---|---|
|
|
FastQC - a quality control tool for high throughput sequence data
FastQC - a quality control tool for high throughput sequence data ===================================== FastQC aims to provide a simple way to do some quality control checks on raw sequence data coming from high throughput sequencing pipelines. It provides a modular set of analyses which you can use to give a quick impression of whether your data has any problems of which you should be aware before doing any further analysis. The main functions of FastQC are: - Import of data from FastQ files (any variant) - Providing a quick overview to tell you in which areas there may be problems - Summary graphs and tables to quickly assess your data - Export of results to an HTML based permanent report - Offline operation to allow automated generation of reports without running the interactive application |
https://github.com/datirium/workflows.git
Path: workflows/fastqc.cwl Branch/Commit ID: 7fb8a1ebf8145791440bc2fed9c5f2d78a19d04c |
|
|
|
kmer_seq_entry_extract_wnode
|
https://github.com/ncbi/pgap.git
Path: task_types/tt_kmer_seq_entry_extract_wnode.cwl Branch/Commit ID: 1e7aa9f0c34987ddafa35f9b1d2c77d99fafbdab |
|
|
|
Cell Ranger Build Reference Indices
Devel version of Cell Ranger Build Reference Indices pipeline ============================================================= |
https://github.com/datirium/workflows.git
Path: workflows/cellranger-mkref.cwl Branch/Commit ID: 7fb8a1ebf8145791440bc2fed9c5f2d78a19d04c |
|
|
|
kmer_build_tree
|
https://github.com/ncbi/pgap.git
Path: task_types/tt_kmer_build_tree.cwl Branch/Commit ID: 90a321ecf2d049330bcf0657cc4d764d2c3f42dd |
|
|
|
Running cellranger count and lineage inference
|
https://github.com/genome/analysis-workflows.git
Path: definitions/subworkflows/single_cell_rnaseq.cwl Branch/Commit ID: 18600518ce6539a2e29c1707392a4c5da5687fa3 |
|
|
|
RNA-Seq pipeline single-read 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 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: 9850a859de1f42d3d252c50e15701928856fe774 |
|
|
|
ani_top_n
|
https://github.com/ncbi/pgap.git
Path: task_types/tt_ani_top_n.cwl Branch/Commit ID: 609aead9804a8f31fa9b3dbc7e52105aec487f31 |
|
|
|
Subworkflow to allow calling different SV callers which require bam files as inputs
|
https://github.com/genome/analysis-workflows.git
Path: definitions/subworkflows/single_sample_sv_callers.cwl Branch/Commit ID: 18600518ce6539a2e29c1707392a4c5da5687fa3 |
|
|
|
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: 7fb8a1ebf8145791440bc2fed9c5f2d78a19d04c |
|
|
|
Trim Galore SMARTer RNA-Seq pipeline paired-end strand specific
https://chipster.csc.fi/manual/library-type-summary.html 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-smarter-dutp.cwl Branch/Commit ID: 581156366f91861bd4dbb5bcb59f67d468b32af3 |
