newQSarray

The features of QSarray can be supplied as a list of objects. The objects in the list must be named appropriately. See <code><a rd-options="" href="/link/QSarray-class?package=qusage&version=2.4.0" data-mini-rdoc="qusage::QSarray-class">QSarray-class</a></code> for a description of the parameters which can be stored in the QSarray object.

The fields of the QSarray object can also be specified individually. If <var>obj</var> is specified and additional fields are provided, the parameters will be combined together into a single QSarray object, with the parameters specified by ... replacing those in <var>obj</var> (this will also produce a warning).


   The constructor for the QSarray object. Should primarily be used internally by <code><a rd-options="" href="/link/qusage?package=qusage&version=2.4.0" data-mini-rdoc="qusage::qusage">qusage</a></code> or <code><a rd-options="" href="/link/makeComparison?package=qusage&version=2.4.0" data-mini-rdoc="qusage::makeComparison">makeComparison</a></code>. See <code><a rd-options="" href="/link/QSarray-class?package=qusage&version=2.4.0" data-mini-rdoc="qusage::QSarray-class">QSarray-class</a></code> for a full description of the fields in the QSarray object.
 

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

newQSarray function

The features of QSarray can be supplied as a list of objects. The objects in the list must be named appropriately. See <code><a href="QSarray-class" rd-options="">QSarray-class</a></code> for a description of the parameters which can be stored in the QSarray object.

The fields of the QSarray object can also be specified individually. If <var>obj</var> is specified and additional fields are provided, the parameters will be combined together into a single QSarray object, with the parameters specified by ...replacing those in <var>obj</var> (this will also produce a warning).

The constructor for the QSarray object. Should primarily be used internally by <code><a href="qusage" rd-options="">qusage</a></code> or <code><a href="makeComparison" rd-options="">makeComparison</a></code>. See <code><a href="QSarray-class" rd-options="">QSarray-class</a></code> for a full description of the fields in the QSarray object.

newQSarray: The qusage Array Object

Description

Usage

Arguments

Details