nf-core/mhcquant
Identify and quantify MHC eluted peptides from mass spectrometry raw data
2.5.0
). The latest
stable release is
2.6.0
.
Introduction
This document describes the output produced by the pipeline. Most of the plots are taken from the MultiQC report, which summarises results at the end 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.
General
*.mzTab
*.tsv
The mzTab output file follows the a HUPO-PSI format and combines all information of the sample-condition group extracted from a database search throughout the pipeline. A detailed explanation of the respective entries are elaborately explained here. MzTab files are compatible with the PRIDE Archive - proteomics data repository and can be uploaded as search files.
MzTab files contain many columns and annotate the most important information - here are a few outpointed:
PEP sequence accession best_search_engine_score[1] retention_time charge mass_to_charge peptide_abundance_study_variable[1]
Most important to know is that in this format we annotated the Comet XCorr of each peptide identification in the best_search_engine_score[1]
column and peptide quantities in the peptide_abundance_study_variable
columns. If --skip_quantification
is specified the best_search_engine_score[1]
holds the percolator q-value.
The TSV output file is an alternative output of OpenMS comprising similar information to the mzTab output. A brief explanation of the structure is listed below. See documentation of the format or PSI documentation for more information about annotated scores and format.
MAP contains information about the different mzML files that were provided initially
#MAP id filename label size
RUN contains information about the search that was performed on each run
#RUN run_id score_type score_direction date_time search_engine_version parameters
PROTEIN contains information about the protein ids corresponding to the peptides that were detected (No protein inference was performed)
#PROTEIN score rank accession protein_description coverage sequence
UNASSIGNEDPEPTIDE contains information about PSMs that were identified but couldn’t be quantified to a precursor feature on MS Level 1
#UNASSIGNEDPEPTIDE rt mz score rank sequence charge aa_before aa_after score_type search_identifier accessions FFId_category feature_id file_origin map_index spectrum_reference COMET:IonFrac COMET:deltCn COMET:deltLCn COMET:lnExpect COMET:lnNumSP COMET:lnRankSP MS:1001491 MS:1001492 MS:1001493 MS:1002252 MS:1002253 MS:1002254 MS:1002255 MS:1002256 MS:1002257 MS:1002258 MS:1002259 num_matched_peptides protein_references target_decoy
CONSENSUS contains information about precursor features that were identified in multiple runs (eg. run 1-3 in this case)
#CONSENSUS rt_cf mz_cf intensity_cf charge_cf width_cf quality_cf rt_0 mz_0 intensity_0 charge_0 width_0 rt_1 mz_1 intensity_1 charge_1 width_1 rt_2 mz_2 intensity_2 charge_2 width_2 rt_3 mz_3 intensity_3 charge_3 width_3
PEPTIDE contains information about peptide hits that were identified and correspond to the consensus features described below
#PEPTIDE rt mz score rank sequence charge aa_before aa_after score_type search_identifier accessions FFId_category fea
Intermediate results
This folder contains the intermediate results from various steps of the MHCquant pipeline (e.g. (un)filtered PSMs, aligned mzMLs, features)
Output files
-
intermediate_results/
-
alignment
: Contains thetrafoXML
files of each run that document the retention time shift after alignment in quantification mode. -
comet
: Contains pin files generated by comet after database search -
percolator
{Sample}_{Condition}_psm.idXML
: File holding extra features that will be used by percolator. Created by PSMFeatureExtractor.{Sample}_{Condition}_pout.idXML
: Unfiltered percolator output.{Sample}_{Condition}_pout_filtered.idXML
: FDR-filtered percolator output.
-
features
: Holds information of quantified features infeatureXML
files as a result of the FeatureFinderIdentification in the quantification mode.
-
-
ion_annotations
-
{Sample}_{Condition}_all_peaks.tsv
: Contains metadata of all measured ions of peptides reported after peptide identification. -
{Sample}_{Condition}_matching_ions.tsv
: Contains ion annotations and additional metadata of peptides reported after peptide identification.
-
-
refined_fdr
(Only if--refine_fdr_on_predicted_subset
is specified)-
*merged_psm_perc_filtered.mzTab
: This file export filtered percolator results (by q-value) as mzTab. -
*_all_ids_merged.mzTab
: Exportas all of the psm results as mztab. -
*perc_subset.idXML
: This file is the outcome of a second OpenMSPercolatorAdapter
run. -
*pred_filtered.idXML
: Contains filtered PSMs prediction results by shrinked search space (outcome mhcflurry). -
{ID}_-_{filename}_filtered
: An outcome file ofOPENMS_IDFILTER_REFINED
.
-
VCF
Reference fasta
Output files
*_vcf.fasta
: If--include_proteins_from_vcf
is specified, then this fasta is created for the respective sample
Neoepitopes
These CSV files list all of the theoretically possible neoepitope sequences from the variants specified in the vcf and neoepitopes that are found during the mass spectrometry search, independant of binding predictions, respectively
Found neoepitopes
Output files
-
class_1_bindings/
*found_neoepitopes_class1.csv
: Generated when--include_proteins_from_vcf
and--predict_class_1
are specified
-
class_2_bindings/
*found_neoepitopes_class2.csv
: Generated when--include_proteins_from_vcf
and--predict_class_2
are specified
This CSV lists all neoepitopes that are found during the mass spectrometry search, independant of binding predictions. The format is as follows:
peptide sequence geneID
vcf_neoepitopes
Output files
-
class_1_bindings/
-
*vcf_neoepitopes_class1.csv
: Generated when--include_proteins_from_vcf
and--predict_class_1
are specified -
class_2_bindings/
-
*vcf_neoepitopes_class2.csv
: Generated when--include_proteins_from_vcf
and--predict_class_2
are specified
This CSV file contains all theoretically possible neoepitope sequences from the variants that were specified in the vcf. The format is shown below
Sequence Antigen ID Variants
Class prediction
Class (1|2) bindings
Output files
-
class_1_bindings/
-
*predicted_peptides_class_1.csv
: If--predict_class_1
is specified, then this CSV is generated -
class_2_bindings/
-
*predicted_peptides_class_2.csv
: If--predict_class_2
is specified, then this CSV is generated
This folder contains the binding predictions of all detected class 1 or 2 peptides and all theoretically possible neoepitope sequences The prediction outputs are comma-separated table (CSV) for each allele, listing each peptide sequence and its corresponding predicted affinity scores:
peptide allele prediction prediction_low prediction_high prediction_percentile
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.html
. - Reports generated by the pipeline:
software_versions.yml
. - Reformatted samplesheet files used as input to the pipeline:
samplesheet.valid.csv
. - Parameters used by the pipeline run:
params.json
.
- 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.