DEqMS: A Method for Accurate Variance Estimation in Differential Protein Expression Analysis

SubCellBarCode: Proteome-wide Mapping of Protein Localization and Relocalization

(2019) Lukas Minus Orre et al.   MOLECULAR CELL

Synaptic markers of cognitive decline in neurodegenerative diseases: a proteomic approach

(2018) Erika Bereczki et al.   BRAIN

Discovery of coding regions in the human genome by integrated proteogenomics analysis workflow

(2018) Yafeng Zhu et al.   Nature Communications

Statistical Models for the Analysis of Isobaric Tags Multiplexed Quantitative Proteomics

(2017) Gina D’Angelo et al.   JOURNAL OF PROTEOME RESEARCH

Isoelectric point-based fractionation by HiRIEF coupled to LC-MS allows for in-depth quantitative analysis of the phosphoproteome

(2017) Elena Panizza et al.   Scientific Reports

ROTS: An R package for reproducibility-optimized statistical testing

(2017) Tomi Suomi et al.   PLoS Computational Biology

microRNAs with AAGUGC seed motif constitute an integral part of an oncogenic signaling network

(2016) Y Zhou et al.   ONCOGENE

Optimization of Statistical Methods Impact on Quantitative Proteomics Data

(2015) Anna Pursiheimo et al.   JOURNAL OF PROTEOME RESEARCH

Orchestrating high-throughput genomic analysis with Bioconductor

(2015) Wolfgang Huber et al.   NATURE METHODS

limma powers differential expression analyses for RNA-sequencing and microarray studies

(2015) Matthew E. Ritchie et al.   NUCLEIC ACIDS RESEARCH

Empirical Bayesian Random Censoring Threshold Model Improves Detection of Differentially Abundant Proteins

(2014) Frank Koopmans et al.   JOURNAL OF PROTEOME RESEARCH

Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ

(2014) Jürgen Cox et al.   MOLECULAR & CELLULAR PROTEOMICS

Ultrasensitive proteome analysis using paramagnetic bead technology

(2014) C. S. Hughes et al.   Molecular Systems Biology

MS-GF+ makes progress towards a universal database search tool for proteomics

(2014) Sangtae Kim et al.   Nature Communications

voom: precision weights unlock linear model analysis tools for RNA-seq read counts

(2014) Charity W Law et al.   GENOME BIOLOGY

Defining, Comparing, and Improving iTRAQ Quantification in Mass Spectrometry Proteomics Data

(2013) Lina Hultin-Rosenberg et al.   MOLECULAR & CELLULAR PROTEOMICS

HiRIEF LC-MS enables deep proteome coverage and unbiased proteogenomics

(2013) Rui M M Branca et al.   NATURE METHODS

Statistical Inference from Multiple iTRAQ Experiments without Using Common Reference Standards

(2012) Shelley M. Herbrich et al.   JOURNAL OF PROTEOME RESEARCH

Addressing Accuracy and Precision Issues in iTRAQ Quantitation

(2010) Natasha A. Karp et al.   MOLECULAR & CELLULAR PROTEOMICS

Differential expression analysis for sequence count data

(2010) Simon Anders et al.   GENOME BIOLOGY

Methods for combining peptide intensities to estimate relative protein abundance

(2009) Brian Carrillo et al.   BIOINFORMATICS

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

(2009) M. D. Robinson et al.   BIOINFORMATICS

Protein Quantification in Label-Free LC-MS Experiments

(2009) Timothy Clough et al.   JOURNAL OF PROTEOME RESEARCH

A Statistical Model for iTRAQ Data Analysis

(2008) Elizabeth G. Hill et al.   JOURNAL OF PROTEOME RESEARCH

Statistical Analysis of Relative Labeled Mass Spectrometry Data from Complex Samples Using ANOVA

(2008) Ann L. Oberg et al.   JOURNAL OF PROTEOME RESEARCH

Mixed-Effects Statistical Model for Comparative LC−MS Proteomics Studies†

(2008) D. S. Daly et al.   JOURNAL OF PROTEOME RESEARCH