DanteR: an extensible R-based tool for quantitative analysis of -omics data

被引：113

作者：

Taverner, Tom ^{[1
]}

Karpievitch, Yuliya V. ^{[1
,2
]}

Polpitiya, Ashoka D. ^{[3
]}

Brown, Joseph N. ^{[1
]}

Dabney, Alan R. ^{[4
]}

Anderson, Gordon A. ^{[1
]}

Smith, Richard D. ^{[1
]}

机构：

[1] Pacific NW Natl Lab, Div Biol Sci, Richland, WA 99352 USA

[2] Univ Tasmania, Sch Math & Phys, Hobart, Tas 7001, Australia

[3] Translat Genom Res Inst, Ctr Prote, Phoenix, AZ 85004 USA

[4] Texas A&M Univ, Dept Stat, College Stn, TX 77843 USA

来源：

BIOINFORMATICS | 2012年 / 28卷 / 18期

基金：

美国国家卫生研究院;

关键词：

NORMALIZATION;

D O I：

10.1093/bioinformatics/bts449

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Motivation: The size and complex nature of mass spectrometry-based proteomics datasets motivate development of specialized software for statistical data analysis and exploration. We present DanteR, a graphical R package that features extensive statistical and diagnostic functions for quantitative proteomics data analysis, including normalization, imputation, hypothesis testing, interactive visualization and peptide-to-protein rollup. More importantly, users can easily extend the existing functionality by including their own algorithms under the Add-On tab.

引用

页码：2404 / 2406

页数：3

共 7 条

[1] Normalization approaches for removing systematic biases associated with mass spectrometry and label-free proteomics [J].

Callister, SJ ;

Barry, RC ;

Adkins, JN ;

Johnson, ET ;

Qian, WJ ;

Webb-Robertson, BJM ;

Smith, RD ;

Lipton, MS .

JOURNAL OF PROTEOME RESEARCH, 2006, 5 (02) :277-286

[2] A statistical framework for protein quantitation in bottom-up MS-based proteomics [J].

Karpievitch, Yuliya ;

Stanley, Jeff ;

Taverner, Thomas ;

Huang, Jianhua ;

Adkins, Joshua N. ;

Ansong, Charles ;

Heffron, Fred ;

Metz, Thomas O. ;

Qian, Wei-Jun ;

Yoon, Hyunjin ;

Smith, Richard D. ;

Dabney, Alan R. .

BIOINFORMATICS, 2009, 25 (16) :2028-2034

[3] Normalization of peak intensities in bottom-up MS-based proteomics using singular value decomposition [J].

Karpievitch, Yuliya V. ;

Taverner, Thomas ;

Adkins, Joshua N. ;

Callister, Stephen J. ;

Anderson, Gordon A. ;

Smith, Richard D. ;

Dabney, Alan R. .

BIOINFORMATICS, 2009, 25 (19) :2573-2580

[4] A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics [J].

Nesvizhskii, Alexey I. .

JOURNAL OF PROTEOMICS, 2010, 73 (11) :2092-2123

[5] DAnTE: a statistical tool for quantitative analysis of -omics data [J].

Polpitiya, Ashoka D. ;

Qian, Wei-Jun ;

Jaitly, Navdeep ;

Petyuk, Vladislav A. ;

Adkins, Joshua N. ;

Camp, David G., II ;

Anderson, Gordon A. ;

Smith, Richard D. .

BIOINFORMATICS, 2008, 24 (13) :1556-1558

[6] GProX, a User-Friendly Platform for Bioinformatics Analysis and Visualization of Quantitative Proteomics Data [J].

Rigbolt, Kristoffer T. G. ;

Vanselow, Jens T. ;

Blagoev, Blagoy .

MOLECULAR & CELLULAR PROTEOMICS, 2011, 10 (08)

[7] Missing value estimation methods for DNA microarrays [J].

Troyanskaya, O ;

Cantor, M ;

Sherlock, G ;

Brown, P ;

Hastie, T ;

Tibshirani, R ;

Botstein, D ;

Altman, RB .

BIOINFORMATICS, 2001, 17 (06) :520-525

← 1 →