iBAQ

The iBAQ calculation is part of the proteinInference script.

It can be used as such:

python pythomics/scripts/proteinInference.py -f /home/chris/ref/celegans/c_elegans.PRJNA13758.WS239.protein.fa -t /home/chris/Chris_wt_peptides_psms.csv --ibaq

Which will perform protein inference, and calculate normalized iBAQ values for each discovered protein. By default, it will look for headers containing the word 'precursor' to find the columns which have precursor measurements. You can specify what columns have precursors as well with the --precursors argument, which accepts a comma separated list of columns such as --precursors 4,6,8,10.

The sample output for this is:

Peptide	PSMS	Total Precursor Area	Proteins	Normalized Precursor Intensity	iBAQ
IEVIEIMTDR	7	4191515000.0	NP_001011724.1;NP_001011725.1...	0.000242027...	0.00001613517369528359018525027167;0.00001613517369528359018525027167;...

This means the proteins NP_... contain the peptide IEVIEIMTDR, and for the iBAQ value, each protein identified is reported. The Protein and iBAQ values are pairwise, meaning they are ordered the same in each column.

And also a file at the protein level (it groups based on your header or regex, ie. for the above, NP_001011724.1 would be an individual grouping)

| Protein | Peptides | Total Precursor Area | Normalized Precursor Intensity | iBAQ | |:-------------:|:-------------:|:-----:|:-------------:|:-------------:|:-----:| | NP_001104026.1 | VANPSGNLTETYVQDR(2) | 4766000 | 0.0017511914... | 0.000125085105638... |

This list can be reduced to only proteins containing unique peptides through the --unique flag.