Removing batch effects from purified plasma cell gene expression microarrays with modified ComBat.

Combining location-and-scale batch effect adjustment with data cleaning by latent factor adjustment. BMC Bioinformatics (2016) 0.76

Statistical significance for genomewide studies. Proc Natl Acad Sci U S A (2003) 88.64

Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics (2006) 22.61

Tackling the widespread and critical impact of batch effects in high-throughput data. Nat Rev Genet (2010) 11.82

A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1. Blood (2006) 7.63

Global gene expression profiling of multiple myeloma, monoclonal gammopathy of undetermined significance, and normal bone marrow plasma cells. Blood (2002) 5.47

International Myeloma Working Group molecular classification of multiple myeloma: spotlight review. Leukemia (2009) 4.91

Gene expression profiling and correlation with outcome in clinical trials of the proteasome inhibitor bortezomib. Blood (2006) 3.39

Removing batch effects in analysis of expression microarray data: an evaluation of six batch adjustment methods. PLoS One (2011) 2.89

The role of maintenance thalidomide therapy in multiple myeloma: MRC Myeloma IX results and meta-analysis. Blood (2011) 2.69

Prediction of survival in multiple myeloma based on gene expression profiles reveals cell cycle and chromosomal instability signatures in high-risk patients and hyperdiploid signatures in low-risk patients: a study of the Intergroupe Francophone du Myélome. J Clin Oncol (2008) 2.68

A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data. Pharmacogenomics J (2010) 2.30

Clinical, genomic, and imaging predictors of myeloma progression from asymptomatic monoclonal gammopathies (SWOG S0120). Blood (2013) 1.98

Gene expression profiling of human plasma cell differentiation and classification of multiple myeloma based on similarities to distinct stages of late-stage B-cell development. Blood (2002) 1.67

Pharmacogenomics of bortezomib test-dosing identifies hyperexpression of proteasome genes, especially PSMD4, as novel high-risk feature in myeloma treated with Total Therapy 3. Blood (2011) 1.61

Homozygous deletion mapping in myeloma samples identifies genes and an expression signature relevant to pathogenesis and outcome. Clin Cancer Res (2010) 1.39

A gene expression signature for high-risk multiple myeloma. Leukemia (2012) 1.36

Testing standard and genetic parameters in 220 patients with multiple myeloma with complete data sets: superiority of molecular genetics. Br J Haematol (2007) 1.28

Batch correction of microarray data substantially improves the identification of genes differentially expressed in rheumatoid arthritis and osteoarthritis. BMC Med Genomics (2012) 0.95

Integrated analysis of multiple microarray datasets identifies a reproducible survival predictor in ovarian cancer. PLoS One (2011) 0.94

Risk stratification in multiple myeloma, part 1: characterization of high-risk disease. Clin Adv Hematol Oncol (2013) 0.85

Five gene probes carry most of the discriminatory power of the 70-gene risk model in multiple myeloma. Leukemia (2014) 0.85