Explore Workflows

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

Path: testdata/workflow_input_sf_expr.cwl

Branch/Commit ID: 141048ae4b78aa765782bb752be4a1550edc2eea

A CWL workflow for discovering known or novel miRNAs from deep sequencing data using the miRDeep2 tool. The ExoCarta exosome database is also used for identifying exosome-related miRNAs, and TargetScan's organism-specific databases are used for identifying miRNA gene targets. ## __Outputs__ #### Primary Output files: - mirs_known.tsv, detected known mature miRNAs, \"Known miRNAs\" tab - mirs_novel.tsv, detected novel mature miRNAs, \"Novel miRNAs\" tab #### Secondary Output files: - mirs_known_exocarta_deepmirs.tsv, list of detected miRNA also in ExoCarta's exosome database, \"Detected Exosome miRNAs\" tab - mirs_known_gene_targets.tsv, pre-computed gene targets of known mature mirs, downloadable - known_mirs_mature.fa, known mature mir sequences, downloadable - known_mirs_precursor.fa, known precursor mir sequences, downloadable - novel_mirs_mature.fa, novel mature mir sequences, downloadable - novel_mirs_precursor.fa, novel precursor mir sequences, downloadable #### Reports: - overview.md (input list, alignment & mir metrics), \"Overview\" tab - mirdeep2_result.html, summary of mirdeep2 results, \"miRDeep2 Results\" tab ## __Inputs__ #### General Info - Sample short name/Alias: unique name for sample - Experimental condition: condition, variable, etc name (e.g. \"control\" or \"20C 60min\") - Cells: name of cells used for the sample - Catalog No.: vender catalog number if available - Bowtie2 index: Bowtie2 index directory of the reference genome. - Reference Genome FASTA: Reference genome FASTA file to be used for alignment. - Genome short name: Name used for setting organism name, genus, species, and tax ID. - Input FASTQ file: FASTQ file from a single-end miRNA sequencing run. #### Advanced - Adapter: Adapter sequence to be trimmed from miRNA sequence reads. (Default: TCGTAT) - Threads: Number of threads to use for steps that support multithreading (Default: 4). ## Hints & Tips: #### For the identification of novel miRNA candidates, the following may be used as a filtering guideline: 1. miRDeep score > 4 (some authors use 1) 2. not present a match with rfam 3. should present a significant RNAfold (\"yes\") 4. a number of mature reads > 10 5. if applicable, novel mir must be expressed in multiple samples #### For filtering mirbase by organism. | genome | organism | division | name | tree | NCBI-taxid | | ---- | --- | --- | ----------- | ----------- | ----------- | | hg19 | hsa | HSA | Homo sapiens | Metazoa;Bilateria;Deuterostoma;Chordata;Vertebrata;Mammalia;Primates;Hominidae | 9606 | | hg38 | hsa | HSA | Homo sapiens | Metazoa;Bilateria;Deuterostoma;Chordata;Vertebrata;Mammalia;Primates;Hominidae | 9606 | | mm10 | mmu | MMU | Mus musculus | Metazoa;Bilateria;Deuterostoma;Chordata;Vertebrata;Mammalia;Rodentia | 10090 | | rn7 | rno | RNO | Rattus norvegicus | Metazoa;Bilateria;Deuterostoma;Chordata;Vertebrata;Mammalia;Rodentia | 10116 | | dm3 | dme | DME | Drosophila melanogaster | Metazoa;Bilateria;Ecdysozoa;Arthropoda;Hexapoda | 7227 | ## __Data Analysis Steps__ 1. The miRDeep2 Mapper module processes Illumina FASTQ output and maps it to the reference genome. 2. The miRDeep2 miRDeep2 module identifies known and novel (mature and precursor) miRNAs. 3. The ExoCarta database of miRNA found in exosomes is then used to find overlap between mirs_known.tsv and exosome associated miRNAs. 4. Finally, TargetScan organism-specific miRNA gene target database is used to find overlap between mirs_known.tsv and gene targets. ## __References__ 1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245920 2. https://github.com/rajewsky-lab/mirdeep2 3. https://biocontainers.pro/tools/mirdeep2 4. https://www.mirbase.org/ 5. http://exocarta.org/index.html 6. https://www.targetscan.org/vert_80/

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

Path: workflows/mirna-mirdeep2-se.cwl

Branch/Commit ID: 261c0232a7a40880f2480b811ed2d7e89c463869

DESeq2 Multi-factor Analysis Runs DeSeq2 multi-factor analysis with manual control over major parameters

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

Path: workflows/deseq-multi-factor.cwl

Branch/Commit ID: 261c0232a7a40880f2480b811ed2d7e89c463869

Workflow without inputs.

https://github.com/common-workflow-language/cwl-v1.2.git

Path: tests/no-inputs-wf.cwl

Branch/Commit ID: 707ebcd2173889604459c5f4ffb55173c508abb3

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

Path: testdata/step_valuefrom5_wf_with_id_v1_2.cwl

Branch/Commit ID: 141048ae4b78aa765782bb752be4a1550edc2eea

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

Path: testdata/workflow_input_format_expr_v1_2.cwl

Branch/Commit ID: 141048ae4b78aa765782bb752be4a1550edc2eea

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

Path: testdata/count-lines7-single-source-wf_v1_2.cwl

Branch/Commit ID: 141048ae4b78aa765782bb752be4a1550edc2eea

https://github.com/hubmapconsortium/sc-atac-seq-pipeline.git

Path: steps/snapanalysis_setup_and_analyze.cwl

Branch/Commit ID: 102d8cb180bb201d6ef054531a84a764a06c8622

Receive parameter update (e.g., by querying an external source like a configuration or calibration database) or by expert input (e.g., by a member of a telescope team or a simulation pipeline expert).

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

Path: workflows/SetParameterFromExternal.cwl

Branch/Commit ID: 789752af87eb190387ff2acb4c95c7a5cdb961e7

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: 261c0232a7a40880f2480b811ed2d7e89c463869