Introduction

A Nextflow pipeline for processing RNASeq sequencing data.

The pipeline was written by The Bioinformatics & Biostatistics Group at The Francis Crick Institute, London.

Pipeline summary

1. Raw read QC (FastQC)
2. Adapter trimming (cutadapt)
3. Alignment and quantification (RSEM, STAR)
4. Sorting and indexing (SAMtools)
5. Quality control metrics:
   • picard:
     • Groups (AddOrReplaceReadGroups)
     • Duplicates (MarkDuplicates)
     • Library complexity (EstimateLibraryComplexity)
     • Various metrics (CollectRnaSeqMetrics, CollectMultipleMetrics)
   • RSeQC:
     • Samples quality (infer_experiment.py, read_distribution.py, tin.py)
     • Alternative splicing (junction_annotation.py, junction_saturation.py)
     • Mismatch (mismatch_profile.py)
   • RNA-SeQC
6. Preparation for statistical analysis:
   • Create a count matrix (R, SummarizedExperiment)
   • Perform a principal component analysis (R, DESeq2)
7. Collect and present a report (MultiQC)

Documentation

The documentation for the pipeline can be found in the docs/ directory:

1. Installation
2. Design file
3. Pipeline configuration
4. Running the pipeline
5. Output and interpretation of results
6. Troubleshooting

Pipeline DAG

Credits

The pipeline was written by the The Bioinformatics & Biostatistics Group at The Francis Crick Institute, London.

The pipeline was developed by Gavin Kelly, Harshil Patel, Nourdine Bah and Philip East.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.