Introduction
This document describes the output produced by the pooled screens analysis of the pipeline.
The directories listed below will be created in the results directory after the pipeline has finished. All paths are relative to the top-level results directory.
Pipeline overview
The pipeline is built using Nextflow and processes data using the following steps:
- Preprocessing
- FastQC - Read Quality Control
- Counting
- MAGeCK count - Mapping reads to reference
- CNV correction)
- CRISPRcleanR - Copy Number Variation correction and read normalization in case of knock-out screens.
- Gene essentiality
- MAGeCK rra - modified robust ranking aggregation (RRA) algorithm
- MAGeCK mle - maximum-likelihood estimation (MLE) for robust identification of CRISPR-screen hits
- BAGEL2 - Bayes Factor to identify essential genes
- MultiQC - Aggregate report describing results and QC from the whole pipeline
- Pipeline information - Report metrics generated during the workflow execution
Preprocessing
FastQC
Output files
fastqc/
*_fastqc.html
: FastQC report containing quality metrics.*_fastqc.zip
: Zip archive containing the FastQC report, tab-delimited data file and plot images.
FastQC gives general quality metrics about your sequenced reads. It provides information about the quality score distribution across your reads, per base sequence content (%A/T/G/C), adapter contamination and overrepresented sequences. For further reading and documentation see the FastQC help pages.
Counting
MAGeCK count
Output files
mageck/count
*_count.txt
: read counts per sample per sgRNA and gene, tab separated*_count_normalized.txt
: normalized read counts, tab separated*_count_summary.txt
: tab separated summary of the quality controls of the count table*_count_table.log
: log information of the run
CNV correction
CRISPRcleanR normalization
Output files
CRISPRcleanR/normalization
*_norm_table.tsv
: read counts normalized with crisprcleanr*.RData
: RData tables containing corrected counts, fold changes and normalized counts
Gene essentiality computation
MAGeCK mle
Output files
mageck/mle
*_gene_summary.txt
: ranked table of the genes and their associated p-values*_sgrna_summary.txt
: sgRNA ranking results, tab separated file*.log
: log of the run
MAGeCK rra
Output files
mageck/rra
*_gene_summary.txt
: ranked table of the genes and their associated p-values*_count_sgrna_summary.txt
: sgRNA ranking results, tab separated file containing means, p-values*.report.Rmd
: markdown report recapping essential genes*_count_table.log
: log of the run*_scatterview.png
: scatter view of the targeted genes and their logFC*_rank.png
: rank view of the targeted genes
MAGeCK is a computational tool to identify important genes from CRISPR-Cas9 screens.
BAGEL2
Output files
bagel2/fold_change
*.foldchange
: foldchange between the reference and treatment contrast provided
bagel2/bayes_factor
*.bf
: bayes factor per gene
bagel2/precision_recall
*.pr
: precision recall per gene
bagel2/graphs
barplot*.png
: barplot of the bayes factor distributionPR*.png
: precision recall plot (Recall vs FDR)
bagel2 is a computational tool to identify important essential genes for CRISPR-Cas9 screening experiments.
MultiQC
Output files
multiqc/
multiqc_report.html
: a standalone HTML file that can be viewed in your web browser.multiqc_data/
: directory containing parsed statistics from the different tools used in the pipeline.multiqc_plots/
: directory containing static images from the report in various formats.
MultiQC is a visualization tool that generates a single HTML report summarising all samples in your project. Most of the pipeline QC results are visualised in the report and further statistics are available in the report data directory.
Results generated by MultiQC collate pipeline QC from supported tools e.g. FastQC. The pipeline has special steps which also allow the software versions to be reported in the MultiQC output for future traceability. For more information about how to use MultiQC reports, see http://multiqc.info.
Pipeline information
Output files
pipeline_info/
- Reports generated by Nextflow:
execution_report.html
,execution_timeline.html
,execution_trace.txt
andpipeline_dag.dot
/pipeline_dag.svg
. - Reports generated by the pipeline:
pipeline_report.html
,pipeline_report.txt
andsoftware_versions.yml
. Thepipeline_report*
files will only be present if the--email
/--email_on_fail
parameter’s are used when running the pipeline. - Reformatted samplesheet files used as input to the pipeline:
samplesheet.valid.csv
.
- Reports generated by Nextflow:
Nextflow provides excellent functionality for generating various reports relevant to the running and execution of the pipeline. This will allow you to troubleshoot errors with the running of the pipeline, and also provide you with other information such as launch commands, run times and resource usage.