Research plan for ibaqpy library

[ypriverol]

This issue is to organize the work needed for the research plan of the ibaqpy library. ibaqpy is the first library that enables to compute the absolute expression intensity-based (IBAQ) for proteins in python. These are the major features of the library:

• ibaq-based quantification values for plexDDA, DDA-LFQ, and DIA-LFQ, to our knowledge this is the only package the allows that. Previous package in R that was only tested in SWATH aLFQ.
• Previous package aLFQ was in R, but not package in Python.
• Scalable for big data, working with millions of peptide features. All previous efforts were not tested in big datasets.
• SDRF oriented, with sample metadata, enabling to merge considering sample biological, technical replicates and fractions.
• Apart from ibaq, it enables to compute TPA values (total protein approach), and the Proteomics Ruler

Issues that need to be solved:

• Implement additional methods for feature normalization #41
• The peptides when they are acylated in the reports are losing the Acetylation  #34
• normalization and normalization stream should be merged #35
• Select the three biggest datasets for DIA, TMT and LFQ as examples #39
• Benchmark with a good dataset for absolute intensity quantification #42
• Clean code for the next release #40