Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Unsupervised empirical Bayesian multiple testing with external
  covariates   In an empirical Bayesian setting, we provide a new multiple testing method,
useful when an additional covariate is available, that influences the
probability of each null hypothesis being true. We measure the posterior
significance of each test conditionally on the covariate and the data, leading
to greater power. Using covariate-based prior information in an unsupervised
fashion, we produce a list of significant hypotheses which differs in length
and order from the list obtained by methods not taking covariate-information
into account. Covariate-modulated posterior probabilities of each null
hypothesis are estimated using a fast approximate algorithm. The new method is
applied to expression quantitative trait loci (eQTL) data.

32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
35
The categories of this paper are: mtrl-th
5
The categories of this paper are: gr-qc
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph
17
The categories of this paper are: q-fin
19
The categories of this paper are: eess
15
The categories of this paper are: nucl-ex
13
The categories of this paper are: quant-ph
0
The categories of this paper are: hep-ph
1
The categories of this paper are: cs
11
The categories of this paper are: hep-lat
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol
10
The categories of this paper are: q-bio