get_lfsr

get_lfdr

get_svalue

get_qvalue

get_pm

get_psd

get_pp

get_np

get_loglik

get_logLR

get_fitted_g

get_pi0

These functions simply return elements of an ash object, generally without doing any calculations.
(So if the value was not computed during the original call to ash, eg because of how outputlevel was set in the call,
then NULL will be returned.)
Accessing elements in this way
rather than directly from the ash object will help ensure compatability moving forward
(e.g. if the internal structure of the ash object changes during software development.)

The R package 'ashr' implements an Empirical Bayes
approach for large-scale hypothesis testing and false discovery
rate (FDR) estimation based on the methods proposed in
M. Stephens, 2016, "False discovery rates: a new deal",
<DOI:10.1093/biostatistics/kxw041>. These methods can be applied
whenever two sets of summary statistics---estimated effects and
standard errors---are available, just as 'qvalue' can be applied
to previously computed p-values. Two main interfaces are
provided: ash(), which is more user-friendly; and ash.workhorse(),
which has more options and is geared toward advanced users. The
ash() and ash.workhorse() also provides a flexible modeling
interface that can accommodate a variety of likelihoods (e.g.,
normal, Poisson) and mixture priors (e.g., uniform, normal).

Peter Carbonetto

ashr

Methods for Adaptive Shrinkage, using Empirical Bayes

Matthew Stephens

Chaoxing Dai

David Gerard

Mengyin Lu

Lei Sun

Jason Willwerscheid

Nan Xiao

Mazon Zeng

get_lfsr function

<dl><dt>x</dt>
<dd>an ash fit (e.g. from running ash)</dd>
<dt>a</dt>
<dd>an ash fit (e.g. from running ash)</dd></dl>

Arguments

<ul>
<li><code>get_lfsr</code>: local false sign rate</li>
<li><code>get_lfdr</code>: local false discovery rate</li>
<li><code>get_svalue</code>: svalue</li>
<li><code>get_qvalue</code>: qvalue</li>
<li><code>get_pm</code>: posterior mean</li>
<li><code>get_psd</code>: posterior standard deviation</li>
<li><code>get_pp</code>: positive probability</li>
<li><code>get_np</code>: negative probability</li>
<li><code>get_loglik</code>: log-likelihood</li>
<li><code>get_logLR</code>: log-likelihood ratio</li>
<li><code>get_fitted_g</code>: fitted g mixture</li>
<li><code>get_pi0</code>: pi0, the proportion of nulls</li>
</ul>

Functions

Return lfsr from an ash object — get_lfsr

<dl>

<dt>x</dt>
<dd>an ash fit (e.g. from running ash)</dd>


<dt>a</dt>
<dd>an ash fit (e.g. from running ash)</dd>

</dl>

Return lfsr from an ash object

get_lfsr: Return lfsr from an ash object

Description

Usage

Value

Arguments

Functions