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- input are mzXML files from Pride which where analysed as part of the eLife paper. Priority = MHC class I peptides (not class II from Mtb mzXML files).
- 2-3 search engines: comet, myrimatch, (msgf+) for identification of MHC peptides from centroided MS/MS data.
- TPP - peptide prophet and iprophet for rescoring and fdr estimation
- NetMHCcons 1.1 for filtering/verification and annotation of identified peptides
- recomputation of the fdr for verified peptides
- spectrast for swath library creation
- Data visualization (heat map (see figure 2 in eLife) and distribution of predicted HLA binding affinities (see Figure 2—figure supplement 4 and Figure 2—figure supplement 5; other visualization tools are optional)
- Create a R/Bioconductor package for publication as an Application Note in Bioinformatics
The workflow is implemented using the applicake plumbing toolkiet
Open questions :
- how does the output of the workflow looks like:
- meta information about sample
- annotation of the identified peptides
sudo apt-get install git
git clone https://github.com/systemhc/systemhc
git clone https://github.com/SysteMHC/SysteMHC_Binaries
git clone https://github.com/SysteMHC/RnetMHC
git clone https://github.com/SysteMHC/SysteMHC_Data
git clone https://github.com/applicake-tools/applicake
git clone https://github.com/applicake-tools/toolscake
at a later stage we might use git submodules
