fHconfig_sum_update_ptr_parallel

Computation of the sum sum_c(w_c*psi_c) parallelized version

Provides functions for the joint analysis of Q sets of
p-values obtained for the same list of items. This joint analysis is
performed by querying a composite hypothesis, i.e. an arbitrary
complex combination of simple hypotheses, as described in Mary-Huard
et al. (2021) <doi:10.1093/bioinformatics/btab592> and De Walsche et
al.(2023) <doi:10.1101/2024.03.17.585412>. In this approach, the
Q-uplet of p-values associated with each item is distributed as a
multivariate mixture, where each of the 2^Q components corresponds to
a specific combination of simple hypotheses. The dependence between
the p-value series is considered using a Gaussian copula function. A
p-value for the composite hypothesis test is derived from the
posterior probabilities.

Tristan Mary-Huard

Query Composite Hypotheses

Annaig De Walsche

Franck Gauthier

fHconfig_sum_update_ptr_parallel function

<dl><dt>Hconfig</dt>
<dd>list of vector of 0 and 1, corresponding to the configurations</dd>
<dt>NewPrior</dt>
<dd>a double vector containing the prior w_c</dd>
<dt>Logf0Mat</dt>
<dd>a double matrix containing the log(f0(xi_q))</dd>
<dt>Logf1Mat</dt>
<dd>a double matrix containing the log(f1(xi_q))</dd>
<dt>threads_nb</dt>
<dd>an int the number of threads</dd></dl>

Arguments

Computation of the sum sum_c(w_c*psi_c) parallelized version — fHconfig_sum_update_ptr_parallel

<dl>

<dt>Hconfig</dt>
<dd>list of vector of 0 and 1, corresponding to the configurations</dd>


<dt>NewPrior</dt>
<dd>a double vector containing the prior w_c</dd>


<dt>Logf0Mat</dt>
<dd>a double matrix containing the log(f0(xi_q))</dd>


<dt>Logf1Mat</dt>
<dd>a double matrix containing the log(f1(xi_q))</dd>


<dt>threads_nb</dt>
<dd>an int the number of threads</dd>

</dl>

fHconfig_sum_update_ptr_parallel: Computation of the sum sum_c(w_c*psi_c) parallelized version

Description

Usage

Value

Arguments