Last updated: 2024-09-16
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Knit directory: rss-net/
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This page outlines all RSS-NET associated functions and scripts that
are freely available at suwonglab/rss-net/src.
rss_net.m:
Fit the RSS-NET model using a mean-field variational Bayes
algorithm.
make_netmat.m:
Create a “network information” matrix (row: SNP; column: gene) for a
given regulatory network.
make_hpgrid.m:
Create a grid of all possible hyper-parameter combinations for
RSS-NET.
make_logodds.m:
Compute prior log odds, \(\log[\pi_j/(1-\pi_j)]=(\theta_0+\theta\cdot
a_j)\cdot \log(10)\), for each SNP \(j\).
make_sigma.m:
Induce prior variances \(\{\sigma_0^2,\sigma^2\}\) from \(\{\eta,\rho\}\).
rss_varbvsr_bigmem_squarem.m:
Fit an extended RSS-BVSR model in a parallel and memory-efficient
manner.
calc_bf.m:
Compute network enrichment Bayes factor (BF) using RSS-NET model fitting
results.
calc_pp.m:
Compute locus-level association statistic \(P_1\) using RSS-NET model fitting
results.
compute_pip.m:
Compute \(P_1\) given locus definitions
and variational estimates.