nf-core/mhcquant V1.1.0 "Golden Eagle"

v1.2.0 nf-core/mhcquant "Golden Eagle" - 2019/01/19

Added

• Subset FDR refinement option
• Fred2 dependency
• vcf parser and translation to proteins

nf-core/mhcquant V1.1.0 "Black Crow"

Updates since 1.0.0:

• mhcflurry conda package added
• mhcflurry predictions added
• peak picking preprocessing added
• minor changes in default parameters
• few arguments added eg. min_peptide_len, max_peptide_len

nf-core/mhcquant V1.0.0 "Naked Chicken"

This is the initial pipeline release of nf-core/mhcquant "Naked Chicken"!

nfcore/mhcquant is a bioinformatics analysis pipeline used for quantitative processing of data dependant (DDA) peptidomics data.

It was specifically designed to analyse immunopeptidomics data, which deals with the analysis of affinity purified, unspecifically cleaved peptides that have recently been discussed intensively in the context of cancer vaccines. (https://www.nature.com/articles/ncomms13404)

The workflow is based on the OpenMS C++ framework for computational mass spectrometry. RAW files (mzML) serve as inputs and a database search (Comet) is performed based on a given input protein database. FDR rescoring is applied using Percolator 3.0 based on a competitive target-decoy approach (reversed decoys). For label free quantification all input files undergo identification based retention time alignment (MapAlignerIdentification), and targeted feature extraction matching ids between runs (FeatureFinderIdentification).

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.