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 …

[图书][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 …

A survey on filter techniques for feature selection in gene expression microarray analysis

C Lazar, J Taminau, S Meganck… - … ACM transactions on …, 2012 - ieeexplore.ieee.org
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 …

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 …

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 …

Statistical challenges in functional genomics

P Sebastiani, E Gussoni, IS Kohane… - Statistical …, 2003 - projecteuclid.org
On February 12, 2001 the Human Genome Project announced the completion of a draft
physical map of the human genome---the genetic blueprint for a human being. Now the …

A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays

GJ McLachlan, RW Bean, LBT Jones - Bioinformatics, 2006 - academic.oup.com
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 …

[HTML][HTML] How many replicates of arrays are required to detect gene expression changes in microarray experiments? A mixture model approach

W Pan, J Lin, CT Le - Genome biology, 2002 - Springer
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 …

A note on using permutation-based false discovery rate estimates to compare different analysis methods for microarray data

Y Xie, W Pan, AB Khodursky - Bioinformatics, 2005 - academic.oup.com
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 …

[HTML][HTML] Model-based cluster analysis of microarray gene-expression data

W Pan, J Lin, CT Le - Genome biology, 2002 - Springer
Background Microarray technologies are emerging as a promising tool for genomic studies.
The challenge now is how to analyze the resulting large amounts of data. Clustering …