Raw-QC

Institut Curie - Nextflow raw-qc analysis pipeline

Introduction

The main goal of the raw-qc pipeline is to perform quality controls on raw sequencing reads, regardless the sequencing application. It was designed to help sequencing facilities to validate the quality of the generated data.

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

3'/5' adapter Trimming

Several steps of trimming can be performed according to the specified options.

1. 3' adapter trimming (with TrimGalore! or fastp)
2. 5' adapter trimming with cutadapt
3. PolyA tail trimming (with cutadapt or fastp)

Additional options can be specified to define the type of sequencing and the minimum quality/length thresholds.

In addition, raw-qc also provides a few presets for automatic clipping/trimming:

• --picoV2, add 3/5prime end clipping
• --rnaLig, add 3/5prime end clipping
• --smartSeqV4, remove 3/5prime adapters

See the usage page for details.

PDX model

In the context of Mouse xenograft samples, it is strongly recommanded to distinguish Mouse from Human reads in order to avoid data misalignment. To do so, raw-qc implements the xengsort tool (--pdx) which generates in output distinct fastq files for both genomes. These new fastq files can then be used for downstream alignment and analysis.

Pipline summary

1. Run quality control of raw sequencing reads (fastqc)
2. Trim sequencing adapters (TrimGalore! / fastp
3. Run quality control of trimmed sequencing reads (fastqc)
4. Run first mapping screen on know references and sources of contamination (fastq Screen)
5. Separate host/graft reads for PDX model (xengsort)
6. Present all QC results in a final report (MultiQC)

Quick help

N E X T F L O W  ~  version 21.10.6
Launching `main.nf` [distracted_curie] - revision: dc75952132
------------------------------------------------------------------------

  ______                      _____ _____ 
  | ___ \                    |  _  /  __ \
  | |_/ /__ ___      ________| | | | /  \/
  |    // _  \ \ /\ / /______| | | | |    
  | |\ \ (_| |\ V  V /       \ \/  / \__/\
  \_| \_\__,_| \_/\_/         \_/\_\\____/
			
                v3.0.0
------------------------------------------------------------------------
							   
Usage:
The typical command for running the pipeline is as follows:
									   
nextflow run main.nf --samplePlan PATH -profile STRING OPTIONS

MANDATORY ARGUMENTS:
   --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)

INPUTS:
   --pdx                 Deconvolute host/graft reads for PDX samples
   --singleEnd           For single-end input data
	
TRIMMING:
   --adapter   STRING [auto, truseg, nextera, smallrna, *]   Type of 3prime adapter to trim
   --adapter5  STRING                                        Specified cutadapt options for 5prime adapter trimming
   --minLen    INTEGER                                       Minimum length of trimmed sequences
   --nTrim                                                   Trim poly-N sequence at the end of the reads
   --qualTrim  INTEGER                                       Minimum mapping quality for trimming
   --twoColour                                               Trimming for NextSeq/NovaSeq sequencers
   --trimTool  STRING [trimgalore, fastp]                    Tool for 3prime adapter trimming and auto-detection

PRESET:
   --picoV2               Preset of clipping parameters for picoV2 protocol
   --polyA                Preset for polyA tail trimming
   --rnaLig               Preset for RNA ligation protocol
   --smartSeqV4           Preset for smartSeqV4 RNA-seq protocol

REFERENCES:
   --genomeAnnotationPath PATH   Path to genome annotations folder

SKIP OPTIONS:
   --skipFastqcRaw              Disable FastQC
   --skipFastqScreen            Disable FastqScreen
   --skipFastqcTrim             Disable FastQC
   --skipMultiqc                Disable MultiQC
   --skipTrimming               Disable Trimming

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 `--singularityPath` 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 the test dataset

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

nextflow run main.nf -profile conda,test --genomeAnnotationPaths 'ANNOTATION_FOLDER'

Run the pipeline from a sample plan

nextflow run main.nf --samplePlan MY_SAMPLE_PLAN --outDir MY_OUTPUT_DIR -profile conda --genomeAnnotationPaths 'ANNOTATION_FOLDER'

Run the pipeline on a cluster

echo "nextflow run main.nf --reads '*.R{1,2}.fastq.gz' --outDir MY_OUTPUT_DIR -profile singularity,cluster" | qsub -N rawqc

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 --singularityPath SINGULARITY_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 set up and written by the sequencing facility and the bioinformatics platform of the Institut Curie (T. Alaeitabar, D. Desvillechabrol, F. Martin, S. Baulande, N. Servant)

Contacts

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