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workflow graph miRNA-Seq miRDeep2 pipeline

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: 675a3ff982091faf304931e9261aacdbabf51702
workflow graph Seurat Cluster

Seurat Cluster ============== Runs filtering, integration, and clustering analyses for Cell Ranger Count Gene Expression or Cell Ranger Aggregate experiments.

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

Path: workflows/seurat-cluster.cwl

Branch/Commit ID: cbefc215d8286447620664fb47076ba5d81aa47f
workflow graph env-wf2.cwl

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

Path: cwltool/schemas/v1.0/v1.0/env-wf2.cwl

Branch/Commit ID: f207d168f4e7eb4dd2279840d4062ba75d9c79c3
workflow graph tt_kmer_compare_wnode

Pairwise comparison

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

Path: task_types/tt_kmer_compare_wnode.cwl

Branch/Commit ID: c17cac4c046f8ba2b8574a121c44a72d2e6b27e6
workflow graph Unaligned BAM to BQSR and VCF

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

Path: definitions/subworkflows/bam_to_bqsr_no_dup_marking.cwl

Branch/Commit ID: b7d9ace34664d3cedb16f2512c8a6dc6debfc8ca
workflow graph no-inputs-wf.cwl

Workflow without inputs.

 https://github.com/common-workflow-language/cwl-v1.1.git

Path: tests/no-inputs-wf.cwl

Branch/Commit ID: e515226f8ac0f7985cd94dae4a301150adae3050
workflow graph Filter Protein Alignments

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

Path: protein_alignment/wf_align_filter.cwl

Branch/Commit ID: 8af4e2aabf43d5e3c7162efae4ad4649df5601e2
workflow graph exome alignment and somatic variant detection

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

Path: definitions/pipelines/somatic_exome_mouse.cwl

Branch/Commit ID: e2a34d2b8c406db9aed8e49e8bdcf36f51444379
workflow graph cache_asnb_entries

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

Path: task_types/tt_cache_asnb_entries.cwl

Branch/Commit ID: 733ab7198a66a0153d0f03c3022ab53c17325ff8
workflow graph umi molecular alignment workflow

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

Path: definitions/subworkflows/molecular_qc.cwl

Branch/Commit ID: 6a55118f915e24d2ad008c93a02d9de5643f5511