data_p

A dataset with summary statistics p values of 1000 genes for RNAseq and CNV data

datasets

A multivariate Gaussian mixture model framework to integrate multiple types of genomic data and allow modeling of inter-data-type correlations for association analysis. 'IMIX' can be implemented to test whether a disease is associated with genes in multiple genomic data types, such as DNA methylation, copy number variation, gene expression, etc. It can also study the integration of multiple pathways. 'IMIX' uses the summary statistics of association test outputs and conduct integration analysis for two or three types of genomics data. 'IMIX' features statistically-principled model selection, global FDR control and computational efficiency. Details are described in Ziqiao Wang and Peng Wei (2020) <doi:10.1093/bioinformatics/btaa1001>.

Ziqiao Wang

IMIX

Gaussian Mixture Model for Multi-Omics Data Integration

Peng Wei

data_p function

A data matrix with 1000 rows and 2 variables:<dl>
<dt>p.rnaseq</dt>
<dd>P values of data type 1 for all genes</dd><dt>p.cnv</dt>
<dd>P values of data type 2 for all genes</dd>
</dl>

Format

P value matrix of two data types — data_p

A data matrix with 1000 rows and 2 variables:<dl>
<dt>p.rnaseq</dt>
<dd>P values of data type 1 for all genes</dd>

<dt>p.cnv</dt>
<dd>P values of data type 2 for all genes</dd>


</dl>

data_p: P value matrix of two data types

Description

Usage

Arguments

Format