Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data

STAT1-Dependent Signal Integration between IFNγ and TLR4 in Vascular Cells Reflect Pro-Atherogenic Responses in Human Atherosclerosis

(2014) Stefan Chmielewski et al.   PLoS One

Quality assessment and data handling methods for Affymetrix Gene 1.0 ST arrays with variable RNA integrity

(2013) Katie S Viljoen et al.   BMC GENOMICS

Resolving the polymorphism-in-probe problem is critical for correct interpretation of expression QTL studies

(2013) Adaikalavan Ramasamy et al.   NUCLEIC ACIDS RESEARCH

Genome-wide Transcriptome Profiling Reveals the Functional Impact of Rare De Novo and Recurrent CNVs in Autism Spectrum Disorders

(2012) Rui Luo et al.   AMERICAN JOURNAL OF HUMAN GENETICS

The sva package for removing batch effects and other unwanted variation in high-throughput experiments

(2012) Jeffrey T. Leek et al.   BIOINFORMATICS

Direct integration of intensity-level data from Affymetrix and Illumina microarrays improves statistical power for robust reanalysis

(2012) Arran K Turnbull et al.   BMC Medical Genomics

Batch effect removal methods for microarray gene expression data integration: a survey

(2012) C. Lazar et al.   BRIEFINGS IN BIOINFORMATICS

Analyzing Illumina Gene Expression Microarray Data from Different Tissues: Methodological Aspects of Data Analysis in the MetaXpress Consortium

(2012) Claudia Schurmann et al.   PLoS One

Using control genes to correct for unwanted variation in microarray data

(2011) J. A. Gagnon-Bartsch et al.   BIOSTATISTICS

Batch effect correction for genome-wide methylation data with Illumina Infinium platform

(2011) Zhifu Sun et al.   BMC Medical Genomics

Removing Batch Effects in Analysis of Expression Microarray Data: An Evaluation of Six Batch Adjustment Methods

(2011) Chao Chen et al.   PLoS One

Correcting for intra-experiment variation in Illumina BeadChip data is necessary to generate robust gene-expression profiles

(2010) Robert R Kitchen et al.   BMC GENOMICS

Tackling the widespread and critical impact of batch effects in high-throughput data

(2010) Jeffrey T. Leek et al.   NATURE REVIEWS GENETICS

Genetics and Beyond – The Transcriptome of Human Monocytes and Disease Susceptibility

(2010) Tanja Zeller et al.   PLoS One

lumi: a pipeline for processing Illumina microarray

(2008) P. Du et al.   BIOINFORMATICS

Sources of variation in baseline gene expression levels from toxicogenomics study control animals across multiple laboratories

(2008) Michael J Boedigheimer et al.   BMC GENOMICS

Empirical Bayes accomodation of batch-effects in microarray data using identical replicate reference samples: application to RNA expression profiling of blood from Duchenne muscular dystrophy patients

(2008) Wynn L Walker et al.   BMC GENOMICS