@COMMENT This bibtex publication entry came from Jeff Bilmes's publication pages at @COMMENT http://melodi.ee.washington.edu/~bilmes @COMMENT The complete bibfile can be found at: @COMMENT http://melodi.ee.washington.edu/~bilmes/bib/bilmes.bib @COMMENT - @Article{Lu2021.01.29.428872, author = {Lu, Yang Young and Bilmes, Jeff and Rodriguez-Mias, Ricard A and Vill{\'e}n, Judit and Noble, William Stafford}, title = {DIAmeter: Matching peptides to data-independent acquisition mass spectrometry data}, elocation-id = {2021.01.29.428872}, year = {2021}, doi = {10.1101/2021.01.29.428872}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Tandem mass spectrometry data acquired using data independent acquisition (DIA) is challenging to interpret because the data exhibits complex structure along both the mass-to-charge (m/z) and time axes. The most common approach to analyzing this type of data makes use of a library of previously observed DIA data patterns (a {\textquotedblleft}spectral library{\textquotedblright}), but this approach is expensive because the libraries do not typically generalize well across laboratories. Here we propose DIAmeter, a search engine that detects peptides in DIA data using only a peptide sequence database. Unlike other library-free DIA analysis methods, DIAmeter supports data generated using both wide and narrow isolation windows, can readily detect peptides containing post-translational modifications, can analyze data from a variety of instrument platforms, and is capable of detecting peptides even in the absence of detectable signal in the survey (MS1) scan.Competing Interest StatementThe authors have declared no competing interest.}, URL = {https://www.biorxiv.org/content/early/2021/01/31/2021.01.29.428872}, eprint = {https://www.biorxiv.org/content/early/2021/01/31/2021.01.29.428872.full.pdf}, journal = {bioRxiv}, }