Ambiguous_Colocalization

<p>An example result from one of our real data applications, which shows an ambiguous colocalization between eQTL and GWAS.</p>

datasets

A multi-task learning approach to variable selection regression with highly correlated predictors and sparse effects,
based on frequentist statistical inference. It provides statistical evidence to identify which subsets of predictors have non-zero
effects on which subsets of response variables, motivated and designed for colocalization analysis across genome-wide association studies (GWAS)
and quantitative trait loci (QTL) studies.
The ColocBoost model is described in Cao et. al. (2025) <doi:10.1101/2025.04.17.25326042>.

Xuewei Cao

colocboost

Multi-Context Colocalization Analysis for QTL and GWAS Studies

Haochen Sun

Ru Feng

Daniel Nachun

Kushal Dey

Gao Wang

Ambiguous_Colocalization function


<div class="section" id="ambiguous-colocalization">
<h3><code>Ambiguous_Colocalization</code></h3><p></p><p>
</p><p>A list with 2 elements</p><dl>
<dt>ColocBoost_Results</dt>
<dd><p>A <code>colocboost</code> output object</p></dd><p></p><p><dt>SuSiE_Results</dt>
<dd><p>Two <code>susie</code> output object for eQTL and GWAS</p></dd></p><p><dt>COLOC_V5_Results</dt>
<dd><p>A <code>coloc</code> output object</p></dd></p><p>
</p></dl><p></p><p></p></div>


Format

A real data example includes an ambiguous colocalization between eQTL and GWAS — Ambiguous_Colocalization


<div class='section' id='ambiguous-colocalization'>
<h3><code>Ambiguous_Colocalization</code></h3>


<p>A list with 2 elements</p><dl>
<dt>ColocBoost_Results</dt>
<dd><p>A <code>colocboost</code> output object</p></dd>

<dt>SuSiE_Results</dt>
<dd><p>Two <code>susie</code> output object for eQTL and GWAS</p></dd>

<dt>COLOC_V5_Results</dt>
<dd><p>A <code>coloc</code> output object</p></dd>


</dl>

</div>


Ambiguous_Colocalization: A real data example includes an ambiguous colocalization between eQTL and GWAS

Description

Usage

Arguments

Format

`Ambiguous_Colocalization`

See Also