Cargando…
Improved quality control processing of peptide-centric LC-MS proteomics data
Motivation: In the analysis of differential peptide peak intensities (i.e. abundance measures), LC-MS analyses with poor quality peptide abundance data can bias downstream statistical analyses and hence the biological interpretation for an otherwise high-quality dataset. Although considerable effort...
Autores principales: | Matzke, Melissa M., Waters, Katrina M., Metz, Thomas O., Jacobs, Jon M., Sims, Amy C., Baric, Ralph S., Pounds, Joel G., Webb-Robertson, Bobbie-Jo M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3187650/ https://www.ncbi.nlm.nih.gov/pubmed/21852304 http://dx.doi.org/10.1093/bioinformatics/btr479 |
Ejemplares similares
-
Combined Statistical Analyses of Peptide Intensities and Peptide Occurrences Improves Identification of Significant Peptides from MS-Based Proteomics Data
por: Webb-Robertson, Bobbie-Jo M., et al.
Publicado: (2010) -
MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses
por: Nakayasu, Ernesto S., et al.
Publicado: (2016) -
Complex‐centric proteome profiling by SEC‐SWATH‐MS
por: Heusel, Moritz, et al.
Publicado: (2019) -
A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification
por: Wang, Jing, et al.
Publicado: (2013) -
Visualization of LC‐MS/MS proteomics data in MaxQuant
por: Tyanova, Stefka, et al.
Publicado: (2015)