fluVaccine

<code>fluVaccine</code> is a list containing data from two separate Flu Vaccine treatment studies, <code>GSE59635</code> and <code>GSE59654</code>. The top-level list contains two entries, <code>esets</code> and <code>phenoData</code>.
 
 <code>fluVaccine$esets</code> is a list containing two expression matrices. Each matrix, which is labeled with the name of the GEO dataset it originates from, contains rows of gene expression levels and columns of samples.
 
 <code>fluVaccine$phenoData</code> is a list containing two data frames. The rows of each data frame correspond to the columns in the expression matrices, and each data frame contains the following columns:
 <dl>
 <dt>subjectID</dt><dd>The subject ID</dd> <dt>responder</dt><dd>Factor describing the subject's response to flu vaccination, either "high" or "low".</dd> <dt>bloodDrawDay</dt><dd>The day post-vaccination that the sample was taken.</dd> </dl>

datasets

This package is an implementation the Quantitative Set
Analysis for Gene Expression (QuSAGE) method described in
(Yaari G. et al, Nucl Acids Res, 2013). This is a novel Gene
Set Enrichment-type test, which is designed to provide a
faster, more accurate, and easier to understand test for gene
expression studies. qusage accounts for inter-gene correlations
using the Variance Inflation Factor technique proposed by Wu et
al. (Nucleic Acids Res, 2012). In addition, rather than simply
evaluating the deviation from a null hypothesis with a single
number (a P value), qusage quantifies gene set activity with a
complete probability density function (PDF). From this PDF, P
values and confidence intervals can be easily extracted.
Preserving the PDF also allows for post-hoc analysis (e.g.,
pair-wise comparisons of gene set activity) while maintaining
statistical traceability. Finally, while qusage is compatible
with individual gene statistics from existing methods (e.g.,
LIMMA), a Welch-based method is implemented that is shown to
improve specificity. For questions, contact Chris Bolen
(cbolen1@gmail.com) or Steven Kleinstein
(steven.kleinstein@yale.edu)

Christopher Bolen

qusage

qusage: Quantitative Set Analysis for Gene Expression

fluVaccine function

Format

<a href="http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE59635">http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE59635</a>
 <a href="http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE59654">http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE59654</a>

Source

<code>fluVaccine</code> is a list containing data from two separate Flu Vaccine treatment studies, <code>GSE59635</code> and <code>GSE59654</code>. The top-level list contains two entries, <code>esets</code> and <code>phenoData</code>.
 
 <code>fluVaccine$esets</code> is a list containing two expression matrices. Each matrix, which is labeled with the name of the GEO dataset it originates from, contains rows of gene expression levels and columns of samples.
 
 <code>fluVaccine$phenoData</code> is a list containing two data frames. The rows of each data frame correspond to the columns in the expression matrices, and each data frame contains the following columns:
 [object Object],[object Object],[object Object]

fluVaccine: Gene expression sets from Flu Vaccine trials

Description

Usage

Arguments

Format

Source

References