Milestone - Combine data sets from a study for metaproteomics relative quantification (2.15)

Expanding the metaproteomics workflow There are two limitations of the current metaproteomics workflow that limit its utility for the community, (i) peptide sequence identification currently requires a matched metagenome for streamlined query, and (ii) all data sets are treated independently which precludes sample comparisons by relative quantitation. To provide an alternative workflow that removes the requirement for a metagenome, the metaproteomics workflow will use an EMSL developed tool75 that uses a machine learning model to identify peptide sequences de novo, and then uses these sequences to predict taxonomy and derive a pseudo-metagenome for use as the input database (Milestone 2.14). This analysis approach has the potential to greatly expand the metaproteomics data available in the NMDC Data Portal. We will address the relative quantification challenge by expanding the current workflow to combine data sets from within the same experimental study where relative quantitative comparisons can be made (Milestone 2.15).

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microbiomedata / issues

Milestone - Combine data sets from a study for metaproteomics relative quantification (2.15) #503