Identification of somatic and germline variants from tumor and normal sample pairs tutorial
variant-analysis-somatic-variants/somatic-variants-tutorial-workflow
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flowchart TD 0["ℹ️ Input Dataset\nSLGFSK-N_231335_r1_chr5_12_17.fastq"]; style 0 stroke:#2c3143,stroke-width:4px; 1["ℹ️ Input Dataset\nSLGFSK-N_231335_r2_chr5_12_17.fastq"]; style 1 stroke:#2c3143,stroke-width:4px; 2["ℹ️ Input Dataset\nSLGFSK-T_231336_r1_chr5_12_17.fastq"]; style 2 stroke:#2c3143,stroke-width:4px; 3["ℹ️ Input Dataset\nSLGFSK-T_231336_r2_chr5_12_17.fastq"]; style 3 stroke:#2c3143,stroke-width:4px; 4["ℹ️ Input Dataset\nhg19.chr5_12_17.fa"]; style 4 stroke:#2c3143,stroke-width:4px; 5["ℹ️ Input Dataset\nhotspots.bed"]; style 5 stroke:#2c3143,stroke-width:4px; 6["ℹ️ Input Dataset\ncgi_variant_positions.bed"]; style 6 stroke:#2c3143,stroke-width:4px; 7["ℹ️ Input Dataset\n01-Feb-2019-CIVic.bed"]; style 7 stroke:#2c3143,stroke-width:4px; 8["ℹ️ Input Dataset\ndbsnp.b147.chr5_12_17.vcf.gz"]; style 8 stroke:#2c3143,stroke-width:4px; 9["ℹ️ Input Dataset\nUniprot_Cancer_Genes.13Feb2019.txt"]; style 9 stroke:#2c3143,stroke-width:4px; 10["ℹ️ Input Dataset\ncgi_genes.txt"]; style 10 stroke:#2c3143,stroke-width:4px; 11["ℹ️ Input Dataset\n01-Feb-2019-GeneSummaries.tsv"]; style 11 stroke:#2c3143,stroke-width:4px; 12["FastQC"]; 0 -->|output| 12; 13["FastQC"]; 1 -->|output| 13; 14["Trimmomatic"]; 0 -->|output| 14; 1 -->|output| 14; 15["FastQC"]; 2 -->|output| 15; 16["FastQC"]; 3 -->|output| 16; 17["Trimmomatic"]; 2 -->|output| 17; 3 -->|output| 17; 18["FastQC"]; 14 -->|fastq_out_r2_paired| 18; 19["FastQC"]; 14 -->|fastq_out_r1_paired| 19; 20["Map with BWA-MEM"]; 14 -->|fastq_out_r1_paired| 20; 14 -->|fastq_out_r2_paired| 20; 21["MultiQC"]; 13 -->|text_file| 21; 15 -->|text_file| 21; 16 -->|text_file| 21; 12 -->|text_file| 21; 22["FastQC"]; 17 -->|fastq_out_r1_paired| 22; 23["FastQC"]; 17 -->|fastq_out_r2_paired| 23; 24["Map with BWA-MEM"]; 17 -->|fastq_out_r1_paired| 24; 17 -->|fastq_out_r2_paired| 24; 25["Filter"]; 20 -->|bam_output| 25; 26["MultiQC"]; 19 -->|text_file| 26; 22 -->|text_file| 26; 23 -->|text_file| 26; 18 -->|text_file| 26; 27["Filter"]; 24 -->|bam_output| 27; 28["RmDup"]; 25 -->|out_file1| 28; 29["RmDup"]; 27 -->|out_file1| 29; 30["BamLeftAlign"]; 28 -->|output1| 30; 31["BamLeftAlign"]; 29 -->|output1| 31; 32["CalMD"]; 30 -->|output_bam| 32; 33["CalMD"]; 31 -->|output_bam| 33; 34["Filter"]; 32 -->|calmd_output| 34; 35["Filter"]; 33 -->|calmd_output| 35; 36["VarScan somatic"]; 34 -->|out_file1| 36; 35 -->|out_file1| 36; 37["SnpEff eff:"]; 36 -->|output| 37; 38["GEMINI load"]; 37 -->|snpeff_output| 38; 39["GEMINI annotate"]; 36 -->|output| 39; 38 -->|outfile| 39; 40["GEMINI annotate"]; 8 -->|output| 40; 39 -->|outfile| 40; 41["GEMINI annotate"]; 5 -->|output| 41; 40 -->|outfile| 41; 42["GEMINI annotate"]; 7 -->|output| 42; 41 -->|outfile| 42; 43["GEMINI annotate"]; 6 -->|output| 43; 42 -->|outfile| 43; 44["GEMINI query"]; 43 -->|outfile| 44; 45["GEMINI query"]; 43 -->|outfile| 45; 46["GEMINI query"]; 43 -->|outfile| 46; 47["GEMINI query"]; 43 -->|outfile| 47; 48["Join"]; 47 -->|outfile| 48; 9 -->|output| 48; 49["Join"]; 48 -->|output| 49; 10 -->|output| 49; 50["Join"]; 49 -->|output| 50; 11 -->|output| 50; 51["Column arrange"]; 50 -->|output| 51; 65d87994-25fd-4e05-b3b0-ad7cd7f3a723["Output\ngene_report_output"]; 51 --> 65d87994-25fd-4e05-b3b0-ad7cd7f3a723; style 65d87994-25fd-4e05-b3b0-ad7cd7f3a723 stroke:#2c3143,stroke-width:4px;
Inputs
Input | Label |
---|---|
SLGFSK-N_231335_r1_chr5_12_17.fastq | SLGFSK-N_231335_r1_chr5_12_17.fastq |
SLGFSK-N_231335_r2_chr5_12_17.fastq | SLGFSK-N_231335_r2_chr5_12_17.fastq |
SLGFSK-T_231336_r1_chr5_12_17.fastq | SLGFSK-T_231336_r1_chr5_12_17.fastq |
SLGFSK-T_231336_r2_chr5_12_17.fastq | SLGFSK-T_231336_r2_chr5_12_17.fastq |
hg19.chr5_12_17.fa | hg19.chr5_12_17.fa |
hotspots.bed | hotspots.bed |
cgi_variant_positions.bed | cgi_variant_positions.bed |
01-Feb-2019-CIVic.bed | 01-Feb-2019-CIVic.bed |
dbsnp.b147.chr5_12_17.vcf.gz | dbsnp.b147.chr5_12_17.vcf.gz |
Uniprot_Cancer_Genes.13Feb2019.txt | Uniprot_Cancer_Genes.13Feb2019.txt |
cgi_genes.txt | cgi_genes.txt |
01-Feb-2019-GeneSummaries.tsv | 01-Feb-2019-GeneSummaries.tsv |
Outputs
From | Output | Label |
---|---|---|
toolshed.g2.bx.psu.edu/repos/bgruening/column_arrange_by_header/bg_column_arrange_by_header/0.2 | Column arrange |
Tools
To use these workflows in Galaxy you can either click the links to download the workflows, or you can right-click and copy the link to the workflow which can be used in the Galaxy form to import workflows.
Importing into Galaxy
Below are the instructions for importing these workflows directly into your Galaxy server of choice to start using them!Hands-on: Importing a workflow
- Click on Workflow on the top menu bar of Galaxy. You will see a list of all your workflows.
- Click on galaxy-upload Import at the top-right of the screen
- Provide your workflow
- Option 1: Paste the URL of the workflow into the box labelled “Archived Workflow URL”
- Option 2: Upload the workflow file in the box labelled “Archived Workflow File”
- Click the Import workflow button
Below is a short video demonstrating how to import a workflow from GitHub using this procedure:
Version History
Version | Commit | Time | Comments |
---|---|---|---|
1 | caffacad4 | 2020-10-10 20:50:51 | Somatic variants tutorial updates (#2054) |
For Admins
Installing the workflow tools
wget https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/somatic-variants/workflows/somatic_variants_tutorial_workflow.ga -O workflow.ga workflow-to-tools -w workflow.ga -o tools.yaml shed-tools install -g GALAXY -a API_KEY -t tools.yaml workflow-install -g GALAXY -a API_KEY -w workflow.ga --publish-workflows