Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Statistical computation methods for microbiome compositional data
  network inference   Microbes can affect processes from food production to human health. Such
microbes are not isolated, but rather interact with each other and establish
connections with their living environments. Understanding these interactions is
essential to an understanding of the organization and complex interplay of
microbial communities, as well as the structure and dynamics of various
ecosystems. A common and essential approach toward this objective involves the
inference of microbiome interaction networks. Although network inference
methods in other fields have been studied before, applying these methods to
estimate microbiome associations based on compositional data will not yield
valid results. On the one hand, features of microbiome data such as
compositionality, sparsity and high-dimensionality challenge the data
normalization and the design of computational methods. On the other hand,
several issues like microbial community heterogeneity, external environmental
interference and biological concerns also make it more difficult to deal with
the network inference. In this paper, we provide a comprehensive review of
emerging microbiome interaction network inference methods. According to various
assumptions and research targets, estimated networks are divided into four main
categories: correlation networks, conditional correlation networks, mixture
networks and differential networks. Their scope of applications, advantages and
limitations are presented in this review. Since real microbial interactions can
be complex and dynamic, no unifying method has captured all the aspects of
interest to date. In addition, we discuss the challenges now confronting
current microbial associations study and future prospects. Finally, we
highlight that the research in microbial network inference requires the joint
promotion of statistical computation methods and experimental techniques.

25
The categories of this paper are: patt-sol
12
The categories of this paper are: nucl-th
20
The categories of this paper are: acc-phys
30
The categories of this paper are: q-alg
19
The categories of this paper are: eess
10
The categories of this paper are: q-bio
14
The categories of this paper are: math-ph
3
The categories of this paper are: physics
1
The categories of this paper are: cs
9
The categories of this paper are: nlin
4
The categories of this paper are: cond-mat
34
The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an
6
The categories of this paper are: astro-ph
7
The categories of this paper are: hep-th
23
The categories of this paper are: solv-int