Detecting significant changes in protein abundance
Tài liệu tham khảo
Urfer, 2006, Statistics for proteomics: a review of tools for analyzing experimental data, Proteomics, 6, 48, 10.1002/pmic.200600554
Keshamouni, 2006, Differential protein expression profiling by iTRAQ-2DLC–MS/MS of lung cancer cells undergoing epithelial–mesenchymal transition reveals a migratory/invasive phenotype, J Proteome Res, 5, 1143, 10.1021/pr050455t
Gan, 2007, Technical, experimental, and biological variations in isobaric tags for relative and absolute quantitation (iTRAQ), J Proteome Res, 6, 821, 10.1021/pr060474i
Prakash, 2007, Assessing bias in experiment design for large scale mass spectrometry-based quantitative proteomics, Mol Cell Proteomics, 6, 1741, 10.1074/mcp.M600470-MCP200
Vitek, 2009, Getting started in computational mass spectrometry-based proteomics, PLoS Comput Biol, 5, e1000366, 10.1371/journal.pcbi.1000366
Kaell, 2011, Computational mass spectrometry-based proteomics, PLoS Comput Biol, 7, e1002277, 10.1371/journal.pcbi.1002277
Oberg, 2008, Statistical analysis of relative labeled mass spectrometry data from complex samples using ANOVA, J Proteome Res, 7, 225, 10.1021/pr700734f
Hill, 2008, A statistical model for iTRAQ data analysis, J Proteome Res, 7, 3091, 10.1021/pr070520u
Kathleen Kerr, 2000, Analysis of variance for gene expression microarray data, J Comput Biol, 7, 819, 10.1089/10665270050514954
Kathleen Kerr, 2001, Experimental design for gene expression microarrays, Biostatistics, 2, 183, 10.1093/biostatistics/2.2.183
Herbrich, 2013, Statistical inference from multiple iTRAQ experiments without using common reference standards, J Proteome Res, 12, 594, 10.1021/pr300624g
Box, 1987, 424
Smyth, 2004, Linear models and empirical Bayes methods for assessing differential expression in microarray experiments, Stat Appl Genet Mol Biol, 3, 10.2202/1544-6115.1027
Brusniak, 2008, Corra: computational framework and tools for LC–MS discovery and targeted mass spectrometry-based proteomics, BMC Bioinform, 9, 542, 10.1186/1471-2105-9-542
Ting, 2009, Normalization and statistical analysis of quantitative proteomics data generated by metabolic labeling, Mol Cell Proteomics, 8, 2227, 10.1074/mcp.M800462-MCP200
Margolin, 2009, Empirical Bayes analysis of quantitative proteomics experiments, PLoS ONE, 4, e7454, 10.1371/journal.pone.0007454
Jankova, 2011, Proteomic comparison of colorectal tumours and non-neoplastic mucosa from paired patient samples using iTRAQ mass spectrometry, Mol Biosyst, 7, 2997, 10.1039/c1mb05236e
Schwaemmle, 2013, Assessment and improvement of statistical tools for comparative proteomics analysis of sparse data sets with few experimental replicates, J Proteome Res, 12, 3874, 10.1021/pr400045u
Zhao, 2013, The application of SILAC mouse in human body fluid proteomics analysis reveals protein patterns associated with IgA nephropathy, Evid Based Complement Altern Med, 2013, 275390, 10.1155/2013/275390
Schwacke, 2009, iQuantitator: a tool for protein expression inference using iTRAQ, BMC Bioinform, 10, 342, 10.1186/1471-2105-10-342
Breitwieser, 2011, General statistical modeling of data from protein relative expression isobaric tags, J Proteome Res, 10, 2758, 10.1021/pr1012784
Chambers, 2012, A cross-platform toolkit for mass spectrometry and proteomics, Nat Biotechnol, 30, 918, 10.1038/nbt.2377
Wang, 2012, OCAP: an open comprehensive analysis pipeline for iTRAQ, Bioinformatics, 28, 1404, 10.1093/bioinformatics/bts150
Gatto, 2012, MSnbase – an R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation, Bioinformatics, 28, 288, 10.1093/bioinformatics/btr645
Gatto, 2014, Using R and Bioconductor for proteomics data analysis, Biochim Biophys Acta, 1844, 42, 10.1016/j.bbapap.2013.04.032
Choi, 2014, MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments, Bioinformatics, 30, 2524, 10.1093/bioinformatics/btu305
Li, 2008, Identification of a bacterial-like HslVU protease in the mitochondria of Trypanosoma brucei and its role in mitochondrial DNA replication, PLoS Pathog, 4, e1000048, 10.1371/journal.ppat.1000048
Liu, 2009, Trypanosomes have six mitochondrial DNA helicases with one controlling kinetoplast maxicircle replication, Mol Cell, 35, 490, 10.1016/j.molcel.2009.07.004
Ringpis, 2011, iCODA: RNAi-based inducible knock-in system in Trypanosoma brucei, Methods Mol Biol, 718, 23, 10.1007/978-1-61779-018-8_2
Ross, 2004, Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents, Mol Cell Proteomics, 3, 1154, 10.1074/mcp.M400129-MCP200
Pierce, 2008, Eight-channel iTRAQ enables comparison of the activity of six leukemogenic tyrosine kinases, Mol Cell Proteomics, 7, 853, 10.1074/mcp.M700251-MCP200
Wang, 2011, Reversed-phase chromatography with multiple fraction concatenation strategy for proteome profiling of human MCF10A cells, Proteomics, 11, 2019, 10.1002/pmic.201000722
Rice, 1995
Benjamini, 1995, Controlling the false discovery rate: a practical and powerful approach to multiple testing, J R Stat Soc Ser B, 57, 289
Storey, 2002, A direct approach to false discovery rates, J R Stat Soc Ser B, 64, 479, 10.1111/1467-9868.00346
Storey, 2003, The positive false discovery rate: a Bayesian interpretation and the q-value, Ann Stat, 31, 2013, 10.1214/aos/1074290335
Storey, 2003, Statistical significance for genomewide studies, Proc Natl Acad Sci USA, 100, 9440, 10.1073/pnas.1530509100
Liu, 2004, A model for random sampling and estimation of relative protein abundance in shotgun proteomics, Anal Chem, 76, 4193, 10.1021/ac0498563
Wang, 2006, Normalization regarding non-random missing values in high-throughput mass spectrometry data, Pac Symp Biocomput, 31, 5
Chong, 2006, Isobaric tags for relative and absolute quantitation (iTRAQ) reproducibility: implication of multiple injections, J Proteome Res, 5, 1232, 10.1021/pr060018u
Jung, 2014, Adaption of the global test idea to proteomics data with missing values, Bioinformatics, 30, 1424, 10.1093/bioinformatics/btu062
Rubin, 1996, Multiple imputation after 18+ years, J Am Stat Assoc, 91, 473, 10.1080/01621459.1996.10476908
Schafer, 1999, Multiple imputation: a primer, Stat Methods Med Res, 8, 3, 10.1191/096228099671525676
Pedreschi, 2008, Treatment of missing values for multivariate statistical analysis of gel-based proteomics data, Proteomics, 8, 1371, 10.1002/pmic.200700975
Albrecht, 2010, Missing values in gel-based proteomics, Proteomics, 10, 1202, 10.1002/pmic.200800576
Karpievitch, 2012, Normalization and missing value imputation for label-free LC–MS analysis, BMC Bioinform, 16, S5, 10.1186/1471-2105-13-S16-S5
