A python toolkit providing best-practice pipelines for fully automated high throughput sequencing analysis. You write a high level configuration file specifying your inputs and analysis parameters. This input drives a parallel pipeline that handles distributed execution, idempotent processing restarts and safe transactional steps. The goal is to provide a shared community resource that handles the data processing component of sequencing analysis, providing researchers with more time to focus on the downstream biology.
ContentsΒΆ
- Getting started
- ----------User stories----------
- Somatic variants
- Bulk RNA-seq expression
- Single cell RNA-seq
- HLA typing
- Germline small variants
- 3prime digital gene expression
- Structural variants
- ChIP/ATAC-seq
- Methylation
- Bulk RNA-seq variants
- Bulk RNA-seq fusions
- fast RNA-seq
- human/mouse disambiguation
- small RNA-seq
- ----------Infrastructure----------
- Installation
- Configuration
- Parallel execution
- Outputs
- Project directory:
- Sample directories:
- Why do I have so many coverage metrics? Which one should I use?
- Interpretation of ontarget_pct vs usable_pct
- Interpretation of mosdepth median coverage vs qualimap median coverage
- Interpretation of bcbio(mosdepth) average target coverage vs qualimap mean coverage
- Downstream analysis
- Common Workflow Language (CWL)
- Cloud
- Development
- ----------Misc----------
- Users
- Internals
- Presentations
- Teaching
- Citations
- Variant calling
- Read alignment
- Interval arithmetics.
- Quality control
- Coverage and callable regions
- SNP and indels in germline (WES, WGS, gene panels)
- Structural and copy number variants in germline (WGS data)
- Somatic small variants
- Somatic copy number variants
- Variant annotation
- bulk RNA-seq
- Fusion calling - RNA-seq
- ATAC-seq
- small RNA-seq