A comparative review of statistical methods for discovering differentially expressed genes in replicated microarray experiments
W Pan - Bioinformatics, 2002 - academic.oup.com
Motivation: A common task in analyzing microarray data is to determine which genes are
differentially expressed across two kinds of tissue samples or samples obtained under two …
differentially expressed across two kinds of tissue samples or samples obtained under two …
[BOOK][B] Large-scale inference: empirical Bayes methods for estimation, testing, and prediction
B Efron - 2012 - books.google.com
We live in a new age for statistical inference, where modern scientific technology such as
microarrays and fMRI machines routinely produce thousands and sometimes millions of …
microarrays and fMRI machines routinely produce thousands and sometimes millions of …
A survey on filter techniques for feature selection in gene expression microarray analysis
A plenitude of feature selection (FS) methods is available in the literature, most of them
rising as a need to analyze data of very high dimension, usually hundreds or thousands of …
rising as a need to analyze data of very high dimension, usually hundreds or thousands of …
Microarrays, empirical Bayes and the two-groups model
B Efron - 2008 - projecteuclid.org
The classic frequentist theory of hypothesis testing developed by Neyman, Pearson and
Fisher has a claim to being the twentieth century's most influential piece of applied …
Fisher has a claim to being the twentieth century's most influential piece of applied …
Size, power and false discovery rates
B Efron - 2007 - projecteuclid.org
Modern scientific technology has provided a new class of large-scale simultaneous
inference problems, with thousands of hypothesis tests to consider at the same time …
inference problems, with thousands of hypothesis tests to consider at the same time …
Normalization and quantification of differential expression in gene expression microarrays
C Steinhoff, M Vingron - Briefings in bioinformatics, 2006 - academic.oup.com
Array-based gene expression studies frequently serve to identify genes that are expressed
differently under two or more conditions. The actual analysis of the data, however, may be …
differently under two or more conditions. The actual analysis of the data, however, may be …
A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays
Motivation: An important problem in microarray experiments is the detection of genes that
are differentially expressed in a given number of classes. We provide a straightforward and …
are differentially expressed in a given number of classes. We provide a straightforward and …
How many replicates of arrays are required to detect gene expression changes in microarray experiments? A mixture model approach
Background It has been recognized that replicates of arrays (or spots) may be necessary for
reliably detecting differentially expressed genes in microarray experiments. However, the …
reliably detecting differentially expressed genes in microarray experiments. However, the …
Consistency of variational Bayes inference for estimation and model selection in mixtures
BE Chérief-Abdellatif, P Alquier - 2018 - projecteuclid.org
Supplement to “Consistency of variational Bayes inference for estimation and model
selection in mixtures”. The supplementary material zip contains the description of a short …
selection in mixtures”. The supplementary material zip contains the description of a short …
A note on using permutation-based false discovery rate estimates to compare different analysis methods for microarray data
Motivation: False discovery rate (FDR) is defined as the expected percentage of false
positives among all the claimed positives. In practice, with the true FDR unknown, an …
positives among all the claimed positives. In practice, with the true FDR unknown, an …