Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Adaptive gPCA: A method for structured dimensionality reduction   When working with large biological data sets, exploratory analysis is an
important first step for understanding the latent structure and for generating
hypotheses to be tested in subsequent analyses. However, when the number of
variables is large compared to the number of samples, standard methods such as
principal components analysis give results which are unstable and difficult to
interpret.
  To mitigate these problems, we have developed a method which allows the
analyst to incorporate side information about the relationships between the
variables in a way that encourages similar variables to have similar loadings
on the principal axes. This leads to a low-dimensional representation of the
samples which both describes the latent structure and which has axes which are
interpretable in terms of groups of closely related variables.
  The method is derived by putting a prior encoding the relationships between
the variables on the data and following through the analysis on the posterior
distributions of the samples. We show that our method does well at
reconstructing true latent structure in simulated data and we also demonstrate
the method on a dataset investigating the effects of antibiotics on the
composition of bacteria in the human gut.

24
The categories of this paper are: dg-ga
10
The categories of this paper are: q-bio
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
34
The categories of this paper are: chem-ph
17
The categories of this paper are: q-fin
9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
20
The categories of this paper are: acc-phys
29
The categories of this paper are: funct-an
21
The categories of this paper are: adap-org
4
The categories of this paper are: cond-mat
22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex