DAnTE: a statistical tool for quantitative analysis of -omics data

Data Analysis Tool Extension (DAnTE) is a statistical tool designed to address challenges associated with quantitative bottom-up, shotgun proteomics data. This tool has also been demonstrated for microarray data and can easily be extended to other high-throughput data types. DAnTE features selected...

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Bibliographic Details
Published in:Bioinformatics Vol. 24; no. 13; pp. 1556 - 1558
Main Authors: Polpitiya, Ashoka D., Qian, Wei-Jun, Jaitly, Navdeep, Petyuk, Vladislav A., Adkins, Joshua N., Camp, David G., Anderson, Gordon A., Smith, Richard D.
Format: Journal Article
Language:English
Published: Oxford Oxford University Press 01.07.2008
Oxford Publishing Limited (England)
Subjects:
Algorithms
Biological and medical sciences
Data Interpretation, Statistical
Databases, Protein
Fundamental and applied biological sciences. Psychology
General aspects
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Peptide Mapping - methods
Proteome - chemistry
Proteomics - methods
Software
Data analysis
Statistical analysis
Bioinformatics
Quantitative analysis
ISSN:1367-4803, 1367-4811, 1460-2059, 1367-4811
Online Access:Get full text
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Description
Summary:Data Analysis Tool Extension (DAnTE) is a statistical tool designed to address challenges associated with quantitative bottom-up, shotgun proteomics data. This tool has also been demonstrated for microarray data and can easily be extended to other high-throughput data types. DAnTE features selected normalization methods, missing value imputation algorithms, peptide-to-protein rollup methods, an extensive array of plotting functions and a comprehensive hypothesis-testing scheme that can handle unbalanced data and random effects. The graphical user interface (GUI) is designed to be very intuitive and user friendly. Availability: DAnTE may be downloaded free of charge at http://omics.pnl.gov/software/ Contact: rds@pnl.gov or proteomics@pnl.gov Supplementary information: An example dataset with instructions on how to perform a series of analysis steps is available at http://omics.pnl.gov/software/
Bibliography:ark:/67375/HXZ-486MN7SQ-B
To whom correspondence should be addressed.
ArticleID:btn217
Associate Editor: John Quackenbush
istex:88855D634D3D079F74DF0C3B76B3746BFAE3463D
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Contact: rds@pnl.gov or proteomics@pnl.gov
ISSN:1367-4803
1367-4811
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btn217