MetaSpectraST: an unsupervised and database-independent analysis workflow for metaproteomic MS/MS data using spectrum clustering.

ABSTRACT:

Background

The high diversity and complexity of the microbial community make it a formidable challenge to identify and quantify the large number of proteins expressed in the community. Conventional metaproteomics approaches largely rely on accurate identification of the MS/MS spectra to their corresponding short peptides in the digested samples, followed by protein inference and subsequent taxonomic and functional analysis of the detected proteins. These approaches are dependent on the availability of protein sequence databases derived either from sample-specific metagenomic data or from public repositories. Due to the incompleteness and imperfections of these protein sequence databases, and the preponderance of homologous proteins expressed by different bacterial species in the co

SUBMITTER: Hao C 

PROVIDER: S-EPMC10405559 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature