msmsEDA
msmsEDA performs exploratory data analysis for liquid chromatography-tandem mass spectrometry (LC-MS/MS) experiments to assess dataset quality and visualize the influence of experimental factors.
Key Features:
- Quality Assessment: Evaluates integrity and reliability of LC-MS/MS datasets to identify data quality issues.
- Visualization Capabilities: Produces visual summaries that reveal patterns, trends, and anomalies in LC-MS/MS data.
- Factor Influence Analysis: Visualizes the impact of experimental factors on LC-MS/MS results to support optimization of conditions.
- Bioconductor Integration: Operates within the Bioconductor ecosystem in R, leveraging interoperable packages for high-throughput data analysis.
Scientific Applications:
- Genomics and Molecular Biology: Supports analysis of LC-MS/MS datasets used in genomics and molecular biology studies.
- Interdisciplinary Bioinformatics and Statistics: Facilitates integration of bioinformatics and statistical methodologies for comprehensive LC-MS/MS data analysis.
Methodology:
Implements analyses within the Bioconductor ecosystem in the R programming language using interoperable packages for high-throughput data analysis.
Topics
Collections
Details
- License:
- GPL-2.0
- Tool Type:
- command-line tool, library
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R
- Added:
- 1/17/2017
- Last Updated:
- 11/25/2024
Operations
Publications
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M. Orchestrating high-throughput genomic analysis with Bioconductor. Nature Methods. 2015;12(2):115-121. doi:10.1038/nmeth.3252. PMID:25633503. PMCID:PMC4509590.