Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bayesian Inference of Networks Across Multiple Sample Groups and Data
  Types   In this paper, we develop a graphical modeling framework for the inference of
networks across multiple sample groups and data types. In medical studies, this
setting arises whenever a set of subjects, which may be heterogeneous due to
differing disease stage or subtype, is profiled across multiple platforms, such
as metabolomics, proteomics, or transcriptomics data. Our proposed Bayesian
hierarchical model first links the network structures within each platform
using a Markov random field prior to relate edge selection across sample
groups, and then links the network similarity parameters across platforms. This
enables joint estimation in a flexible manner, as we make no assumptions on the
directionality of influence across the data types or the extent of network
similarity across the sample groups and platforms. In addition, our model
formulation allows the number of variables and number of subjects to differ
across the data types, and only requires that we have data for the same set of
groups. We illustrate the proposed approach through both simulation studies and
an application to gene expression levels and metabolite abundances on subjects
with varying severity levels of Chronic Obstructive Pulmonary Disease (COPD).

20
The categories of this paper are: acc-phys
36
The categories of this paper are: cmp-lg
29
The categories of this paper are: funct-an
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio
21
The categories of this paper are: adap-org
33
The categories of this paper are: plasm-ph
13
The categories of this paper are: quant-ph
35
The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
1
The categories of this paper are: cs
5
The categories of this paper are: gr-qc
19
The categories of this paper are: eess
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph