Adjustment of systematic microarray data biases

By Mónica Benito, J. Parker, Quan Du, Junyuan Wu, Dong Xiang, Charles M. Perou, James Stephen Marron. Bioinform., 2004

442 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/24022c31a448ee8cee610c5686fb7883c3efb060

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Citations in the corpus

Subtypes of Pancreatic Ductal Adenocarcinoma and Their Differing Responses to Therapy (2011, methodology): “To increase power, we merged these two data sets with the distance-weighted discrimination (DWD) metho”
Key Issues in Conducting a Meta-Analysis of Gene Expression Microarray Datasets (2008, background): “Unsupervised visualization [62] can help to identify any grouping caused by experimental factors.”
A Six-Gene Signature Predicts Survival of Patients with Localized Pancreatic Ductal Adenocarcinoma (2010, methodology): “. A distance weighted discrimination (DWD) was used to detect the systematic biases between the different datasets and then global adjustments made to remove these biases”
Revealing the vectors of cellular identity with single-cell genomics (2016, background): “3d ), and either remove batch terms46,47 (also see https://github.com/YosefLab/scone) or directly incorporate them into downstream analyses (e.g., for detecting differentially expressed genes48,49).”
Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors (2007, methodology): “This dataset was next corrected for systemic biases using distance weighted discrimination [24].”
Batch effect removal methods for microarray gene expression data integration: a survey (2013, methodology): “Distance-weighted discrimination (DWD) [11], an adaptation of Support Vector Machines (SVM) [39], can be used for batch effect removal as follows.”
Removing Batch Effects in Analysis of Expression Microarray Data: An Evaluation of Six Batch Adjustment Methods (2011, background): “, of which we have chosen six for evaluation. Distance-weighted discrimination (DWD)”
Molecular classification of head and neck squamous cell carcinomas using patterns of gene expression. (2004, methodology): “We used “Distance Weighted DisNorth Carolina at Chapel Hill (UNC) Tissue Procurement Core Facility from crimination/DWD” as described in Benito et al. (2004) on the two largest patients undergoing surgery at the UNC Hospital and who consented to sets of samples assayed using two different batches of”
Sparse principal component analysis via regularized low rank matrix approximation (2008, methodology): “Benito et al. (2004) proposed to use DWD (Marron et al., 2005) as a systematic bias adjustment method to eliminate the platform eﬀect of the NCI60 data.”
Systematic noise degrades gene co-expression signals but can be corrected (2015, unknown): “Other tools, like distance weighted discrimination [14], crucially use information on batches in order to clean the data.”