Peek a peak: a glance at statistics for quantitative label-free proteomics

被引:32
作者
Podwojski, Katharina [1 ]
Eisenacher, Martin [1 ]
Kohl, Michael [1 ]
Turewicz, Michael [1 ]
Meyer, Helmut E. [1 ]
Rahnenfuehrer, Joerg [2 ]
Stephan, Christian [1 ]
机构
[1] Ruhr Univ Bochum, Med Proteom Ctr, Zentrum Klin Forsch XKF 1, D-44801 Bochum, Germany
[2] Tech Univ Dortmund, Fachgebiet Stat Methoden Genet & Chemometrie, Fak Stat, D-44221 Dortmund, Germany
关键词
identification; label-free; mass spectrometry; quantification; spectral counting; LC-MS DATA; MASS-SPECTROMETRY; LIQUID-CHROMATOGRAPHY; BIOMARKER DISCOVERY; PROTEIN EXPRESSION; TIME ALIGNMENT; FEATURE-EXTRACTION; ABSOLUTE PROTEIN; PEPTIDE; QUANTIFICATION;
D O I
10.1586/EPR.09.107
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Today, label-free mass spectrometry methods are frequently used for quantification of proteins and peptides. There have been several proposals of measurable parameters that best reflect quantities, such as peak areas as well as spectral counts. This review provides a systematic overview of the proposed methods. Owing to the shotgun proteomics approach generally used today for label-free mass spectrometry, any quantitative measure in the first place is a measure of peptide quantity. There has been no systematic research on how to best infer protein quantity from its measured peptides' quantities. The way peptide identifications are assembled to protein lists may especially lead to significantly different results in protein quantification. A further focus of this review will thus be the assembly of measured peptide quantities to a protein quantity.
引用
收藏
页码:249 / 261
页数:13
相关论文
共 100 条
  • [1] Mass spectrometry-based proteomics
    Aebersold, R
    Mann, M
    [J]. NATURE, 2003, 422 (6928) : 198 - 207
  • [2] UniMaP: finding unique mass and peptide signatures in the human proteome
    Alexandridou, Anastasia
    Tsangaris, George Th.
    Vougas, Konstantinos
    Nikita, Konstantina
    Spyrou, George
    [J]. BIOINFORMATICS, 2009, 25 (22) : 3035 - 3037
  • [3] In vitro and in silico processes to identify differentially expressed proteins
    Allet, N
    Barrillat, N
    Baussant, T
    Boiteau, C
    Botti, P
    Bougueleret, L
    Budin, N
    Canet, D
    Carraud, S
    Chiappe, D
    Christmann, N
    Colinge, J
    Cusin, I
    Dafflon, N
    Depresle, B
    Fasso, I
    Frauchiger, P
    Gaertner, H
    Gleizes, A
    Gonzalez-Couto, E
    Jeandenans, C
    Karmime, A
    Kowall, T
    Lagache, S
    Mahé, E
    Masselot, A
    Mattou, H
    Moniatte, M
    Niknejad, A
    Paolini, M
    Perret, F
    Pinaud, N
    Ranno, F
    Raimondi, S
    Reffas, S
    Regamey, PO
    Rey, PA
    Rodriguez-Tomé, P
    Rose, K
    Rossellat, G
    Saudrais, C
    Schmidt, C
    Villain, M
    Zwahlen, C
    [J]. PROTEOMICS, 2004, 4 (08) : 2333 - 2351
  • [4] Application of wavelet transforms to experimental spectra: Smoothing, denoising, and data set compression
    Barclay, VJ
    Bonner, RF
    Hamilton, IP
    [J]. ANALYTICAL CHEMISTRY, 1997, 69 (01) : 78 - 90
  • [5] A suite of algorithms for the comprehensive analysis of complex protein mixtures using high-resolution LC-MS
    Bellew, Matthew
    Coram, Marc
    Fitzgibbon, Matthew
    Igra, Mark
    Randolph, Tim
    Wang, Pei
    May, Damon
    Eng, Jimmy
    Fang, Ruihua
    Lin, ChenWei
    Chen, Jinzhi
    Goodlett, David
    Whiteaker, Jeffrey
    Paulovich, Amanda
    McIntosh, Martin
    [J]. BIOINFORMATICS, 2006, 22 (15) : 1902 - 1909
  • [6] Protein diversity from alternative splicing: A challenge for bioinformatics and post-genome biology
    Black, DL
    [J]. CELL, 2000, 103 (03) : 367 - 370
  • [7] Biomedical informatics for proteomics
    Boguski, MS
    McIntosh, MW
    [J]. NATURE, 2003, 422 (6928) : 233 - 237
  • [8] A comparison of normalization methods for high density oligonucleotide array data based on variance and bias
    Bolstad, BM
    Irizarry, RA
    Åstrand, M
    Speed, TP
    [J]. BIOINFORMATICS, 2003, 19 (02) : 185 - 193
  • [9] Corra: Computational framework and tools for LC-MS discovery and targeted mass spectrometry-based proteomics
    Brusniak, Mi-Youn
    Bodenmiller, Bernd
    Campbell, David
    Cooke, Kelly
    Eddes, James
    Garbutt, Andrew
    Lau, Hollis
    Letarte, Simon
    Mueller, Lukas N.
    Sharma, Vagisha
    Vitek, Olga
    Zhang, Ning
    Aebersold, Ruedi
    Watts, Julian D.
    [J]. BMC BIOINFORMATICS, 2008, 9 (1)
  • [10] Chromatographic alignment by warping and dynamic programming as a pre-processing tool for PARAFAC modelling of liquid chromatography-mass spectrometry data
    Bylund, D
    Danielsson, R
    Malmquist, G
    Markides, KE
    [J]. JOURNAL OF CHROMATOGRAPHY A, 2002, 961 (02) : 237 - 244