Revision: 1038
http://svn.sourceforge.net/r-gregmisc/?rev=1038&view=rev
Author: warnes
Date: 2006-12-05 08:54:56 -0800 (Tue, 05 Dec 2006)
Log Message:
-----------
Some corrections from review of similar article for RNEWS
Modified Paths:
--------------
trunk/exp.ssize/DESCRIPTION
trunk/exp.ssize/inst/doc/ssize.pdf
trunk/exp.ssize/inst/doc/ssize.tex
Modified: trunk/exp.ssize/DESCRIPTION
===================================================================
--- trunk/exp.ssize/DESCRIPTION 2006-12-05 16:52:38 UTC (rev 1037)
+++ trunk/exp.ssize/DESCRIPTION 2006-12-05 16:54:56 UTC (rev 1038)
@@ -1,7 +1,6 @@
Package: ssize.sim
Title: Estimate Effectivenes of Microarry Sample Size Estimation via Simulation
-Version: 1.0.0
-Date: 2005-01-14
+Version: 1.0.1
Author: Peng Liu and Gregory R. WarneS
Description: Functions for evaluating the performance microarray
sample size estimation procedures via simulation, as used in
Modified: trunk/exp.ssize/inst/doc/ssize.pdf
===================================================================
(Binary files differ)
Modified: trunk/exp.ssize/inst/doc/ssize.tex
===================================================================
--- trunk/exp.ssize/inst/doc/ssize.tex 2006-12-05 16:52:38 UTC (rev 1037)
+++ trunk/exp.ssize/inst/doc/ssize.tex 2006-12-05 16:54:56 UTC (rev 1038)
@@ -36,8 +36,8 @@
\begin{abstract}
-RNA Expression Microarray technology is widely applied in biomedical
-and pharmaceutical research. The huge number of RNA concentrations
+mRNA expression microarray technology is widely applied in biomedical
+and pharmaceutical research. The huge number of mRNA concentrations
estimated for each sample make it difficult to apply traditional
sample size calculation techniques and has left most practitioners
to rely on rule-of-thumb techniques. In this paper, we describe and
@@ -49,11 +49,13 @@
been appropriately selected. Although we demonstrate sample size
calculation only for the two-sample pooled t-test, it is trivial to
substitute an alternative sample size formula appropriate to the
-problem at hand. The described method has been implemented in the
-\texttt{ssize} R package, which is available from the Bioconductor
-project (\url{http://www.bioconductor.org}) web site.
+problem at hand.
+%The described method has been implemented in the
+%\texttt{ssize} R package, which is available from the Bioconductor
+%project (\url{http://www.bioconductor.org}) web site.
+
%\subsection{Motivation:}
%Microarray technology is widely applied in biomedical and
@@ -122,11 +124,11 @@
High-throughput microarray experiments allow the measurement of
expression levels for tens of thousands of genes simultaneously.
These experiments have been used in many disciplines of biological
-research, including as neuroscience \citep{Mandel03},
+research, including neuroscience \citep{Mandel03},
pharmacogenomic research, genetic disease and cancer diagnosis
\citep{Heller02}. As a tool for estimating gene expression and
single nucleotide polymorphism (SNP) genotyping, microarrays produce
-huge amounts of data which are providing important new insights.
+huge amounts of data which can provide important new insights.
Microarray experiments are rather costly in terms of materials
(RNA sample, reagents, chip, etc), laboratory manpower, and data
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.
|
