jump_cutoff

Estimate threshold of maximum p-values across two studies to control FDR.

Implementing a computationally scalable false discovery rate control procedure for replicability analysis based on maximum of p-values. Please cite the manuscript corresponding to this package [Lyu, P. et al., (2023), <https://www.biorxiv.org/content/10.1101/2023.02.13.528417v2>].

Yan Li 

JUMP

Replicability Analysis of High-Throughput Experiments

Pengfei Lyu 

Xiaoquan Wen 

Hongyuan Cao 

jump_cutoff function

<dl><dt>pa_in</dt>
<dd>A numeric vector of p-values from study 1.</dd>
<dt>pb_in</dt>
<dd>A numeric vector of p-values from study 2.</dd>
<dt>xi_in</dt>
<dd>The estimates of proportions of three null components.</dd>
<dt>alpha_in</dt>
<dd>The FDR level to control, default is 0.05.</dd></dl>

Arguments

Estimate threshold of maximum p-values across two studies to control FDR. — jump_cutoff

<dl>

<dt>pa_in</dt>
<dd>A numeric vector of p-values from study 1.</dd>


<dt>pb_in</dt>
<dd>A numeric vector of p-values from study 2.</dd>


<dt>xi_in</dt>
<dd>The estimates of proportions of three null components.</dd>


<dt>alpha_in</dt>
<dd>The FDR level to control, default is 0.05.</dd>

</dl>

jump_cutoff: Estimate threshold of maximum p-values across two studies to control FDR.

Description

Usage

Value

Arguments