RNA-seq

Institut Curie - Nextflow rna-seq analysis pipeline

Introduction

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with conda / singularity containers making installation easier and results highly reproducible.

The first version of this pipeline was modified from the nf-core/rnaseq pipeline. See the nf-core project for more details.

Pipline summary

1. Trim adapters from sequencing reads (TrimGalore!
2. Separate host/graft reads for PDX model (xengsort)
3. Run quality control of sequencing reads (fastqc)
4. Align reads on ribosomal RNAs sequences when available (bowtie1)
5. Align reads on reference genome (STAR / hisat2)
6. Infer reads orientation (rseqc)
7. Dedicated quality controls
   • Saturation curves (preseq / R)
   • Duplicates (picard / dupRadar)
   • Reads annotation (qualimap / R)
   • Gene body coverage (qualimap)
8. Identito monitoring based on a list of known polymorphism (bcftools / R)
9. Generate counts table from aligned data or pseudo-alignment (STAR / featureCounts / HTSeqCounts/salmon)
10. Exploratory analysis (R)
11. Reference-guided de novo transcripts assembly (stringtie, scallop)
12. Present all QC results in a final report (MultiQC)

Quick help

N E X T F L O W  ~  version 20.10.0
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Usage:

The typical command for running the pipeline is as follows:

nextflow run main.nf --reads PATH --samplePlan PATH -profile STRING --genome STRING

MANDATORY ARGUMENTS:
    --genome        STRING                                                                            Name of the reference genome.
    --reads         PATH                                                                              Path to input data (must be surrounded with quotes)
    --samplePlan    PATH                                                                              Path to sample plan (csv format) with raw reads (if `--reads` is not specified)
    --aligner       STRING [star, hisat2]                                                             Tool for reads alignment
    --counts        STRING [star, featureCounts, HTseqCounts, salmon]                                 Tool to use to estimate the raw counts per gene
    --pseudoAligner STRING [salmon]                                                                   Tool for reads pseudo-alignment
		 
INPUTS:
    --singleEnd                                       For single-end input data
    --stranded  STRING [auto, forward, reverse, no]   Library strandness

PREPROCESSING:
    --pdx                Deconvolute host/graft reads for PDX samples
	--trimming           Trim adapters with TrimGalore	

MAPPING:
    --bowtieOpts               STRING    Options for rRNA mapping with bowtie
    --hisat2Opts               STRING    Options for genome mapping with Hisat2
    --saveAlignedIntermediates           Save intermediates alignment files
    --starOpts                 STRING    Options for STAR mapping
    --starTwoPass                        Run STAR in two pass mode

COUNTS:
    --featurecountsOpts STRING   Options for featureCounts quantification
    --htseqOpts         STRING   Options for HTSeq quantification
    --salmonQuantOpts   STRING   Options for Salmon quantification

DE NOVO ASSEMBLY:
    --denovo STRING [stringtie, scallop]  Tool for reference-guided assembly of RNA transcripts
    --scallopOpts  STRING                 Options for Scallop analysis
    --stringtieOps STRING                 Options for Stringtie analysis
		
REFERENCES:
    --bed12                PATH   Path to gene file (BED12)
    --fasta                PATH   Path to genome fasta file
    --fastaFai             PATH   Path to genome index fasta file
    --genomeAnnotationPath PATH   Path to genome annotations folder
    --gtf                  PATH   Path to GTF annotation file
    --hisat2Index          PATH   Path to Hisat2 indexes
    --bowtie2Index         PATH   Path to Bowtie2 indexes
    --polym                PATH   Path to BED file with polymorphisms for identito monitoring
    --rrna                 PATH   Path to Bowtie indexes for rRNA mapping
    --salmonIndex          PATH   Path to Salmon indexes
    --starIndex            PATH   Path to STAR indexes
    --transcriptsFasta     PATH   Path to transcriptome fasta file

SKIP OPTIONS:
    --skipBigWig                       Disable bigwig generation with Deeptools
    --skipMarkDup                      Disable duplicates analysis with Picard/DupRadar
    --skipFastqc                       Disable Fastqc
    --skipGeneCountsAnalysis           Disable exporatory analysis of genes count
    --skipIdentito                     Disable Identito
    --skipMultiqc                      Disable MultiQC
    --skipQC                           Disable quality controls on raw and aligned reads [fastqc, qualimap, preseq]
    --skipQualimap                     Disable RNA-seq quality controls with Qualimap
    --skipRrna                         Disable rRNA mapping
    --skipSaturation                   Disable saturation analysis with Preseq

OTHER OPTIONS:
    --metadata      PATH     Specify a custom metadata file for MultiQC
    --multiqcConfig PATH     Specify a custom config file for MultiQC
    --name          STRING   Name for the pipeline run. If not specified, Nextflow will automatically generate a random mnemonic
    --outDir        PATH     The output directory where the results will be saved
	
=======================================================
Available Profiles
  -profile test                        Run the test dataset
  -profile conda                       Build a new conda environment before running the pipeline. Use `--condaCacheDir` to define the conda cache path
  -profile multiconda                  Build a new conda environment per process before running the pipeline. Use `--condaCacheDir` to define the conda cache path
  -profile path                        Use the installation path defined for all tools. Use `--globalPath` to define the insallation path
  -profile multipath                   Use the installation paths defined for each tool. Use `--globalPath` to define the insallation path
  -profile docker                      Use the Docker images for each process
  -profile singularity                 Use the Singularity images for each process. Use `--singularityImagePath` to define the insallation path
  -profile cluster                     Run the workflow on the cluster, instead of locally
						  

Quick run

The pipeline can be run on any infrastructure from a list of input files or from a sample plan as follow

Run the pipeline on a test dataset

See the conf/test.conf to set your test dataset.

nextflow run main.nf -profile test,conda

Run the pipeline from a sample plan

nextflow run main.nf --samplePlan MY_SAMPLE_PLAN --aligner 'star' --counts 'star' --genome 'hg38' --outDir MY_OUTPUT_DIR -profile conda

Run the pipeline on a computational cluster

echo "nextflow run main.nf --reads '*.R{1,2}.fastq.gz' --aligner 'star' --counts 'star' --genome 'hg19' --outDir MY_OUTPUT_DIR -profile singularity,cluster" | qsub -N rnaseq

Defining the '-profile'

By default (whithout any profile), Nextflow will excute the pipeline locally, expecting that all tools are available from your PATH variable.

In addition, we set up a few profiles that should allow you i/ to use containers instead of local installation, ii/ to run the pipeline on a cluster instead of on a local architecture. The description of each profile is available on the help message (see above).

Here are a few examples of how to set the profile option. See the full documentation for details.

## Run the pipeline locally, using the paths defined in the configuration for each tool (see conf/path.config)
-profile path --globalPath INSTALLATION_PATH 

## Run the pipeline on the cluster, using the Singularity containers
-profile cluster,singularity --singularityImagePath SINGULARITY_IMAGE_PATH 

## Run the pipeline on the cluster, building a new conda environment
-profile cluster,conda --condaCacheDir CONDA_CACHE 

Sample Plan

A sample plan is a csv file (comma separated) that list all samples with their biological IDs, with no header.

SAMPLE_ID,SAMPLE_NAME,PATH_TO_R1_FASTQ,[PATH_TO_R2_FASTQ]

Full Documentation

1. Installation
2. Reference genomes
3. Running the pipeline
4. Output and how to interpret the results
5. Troubleshooting

Credits

This pipeline has been written by the bioinformatics platform of the Institut Curie (P. La Rosa, N. Servant)

Citation

If you use this pipeline for your project, please cite it using the following doi: 10.5281/zenodo.7443721
Do not hesitate to use the Zenodo doi corresponding to the version you used !

Contacts

For any question, bug or suggestion, please use the issues system or contact the bioinformatics core facility.