estimate_null_correlation_simple

Estimates a null correlation matrix from data using
simple z score threshold

Implements the multivariate adaptive shrinkage (mash)
method of Urbut et al (2019) <DOI:10.1038/s41588-018-0268-8> for
estimating and testing large numbers of effects in many conditions
(or many outcomes). Mash takes an empirical Bayes approach to
testing and effect estimation; it estimates patterns of similarity
among conditions, then exploits these patterns to improve accuracy
of the effect estimates. The core linear algebra is implemented in
C++ for fast model fitting and posterior computation.

Peter Carbonetto

mashr

Multivariate Adaptive Shrinkage

Matthew Stephens

Sarah Urbut

Gao Wang

Yuxin Zou

Yunqi Yang

Sam Roweis

David Hogg

Jo Bovy

estimate_null_correlation_simple function

<dl><dt>data</dt>
<dd>a mash data object, eg as created by <code>mash_set_data</code></dd>
<dt>z_thresh</dt>
<dd>the z score threshold below which to call an effect null</dd>
<dt>est_cor</dt>
<dd>whether to estimate correlation matrix (TRUE) or the
covariance matrix (FALSE).</dd></dl>

Arguments

Estimate null correlations (simple) — estimate_null_correlation_simple

<dl>

<dt>data</dt>
<dd>a mash data object, eg as created by <code>mash_set_data</code></dd>


<dt>z_thresh</dt>
<dd>the z score threshold below which to call an effect null</dd>


<dt>est_cor</dt>
<dd>whether to estimate correlation matrix (TRUE) or the
covariance matrix (FALSE).</dd>

</dl>

Estimate null correlations (simple)

estimate_null_correlation_simple: Estimate null correlations (simple)

Description

Usage

Arguments

Details

Examples