Abstract
Microbial community analysis experiments to assess the effect of a treatment intervention (or environmental change) on the relative abundance levels of multiple related microbial species (or operational taxonomic units) simultaneously using high throughput genomics are becoming increasingly common. Within the framework of the evolutionary phylogeny of all species considered in the experiment, this translates to a statistical need to identify the phylogenetic branches that exhibit a significant consensus response (in terms of operational taxonomic unit abundance) to the intervention. We present the R software package SigTree, a collection of flexible tools that make use of meta-analysis methods and regular expressions to identify and visualize significantly responsive branches in a phylogenetic tree, while appropriately adjusting for multiple comparisons.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 372-378 |
| Number of pages | 7 |
| Journal | Computational and Structural Biotechnology Journal |
| Volume | 15 |
| DOIs | |
| State | Published - 2017 |
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Keywords
- Microbial community analysis
- Microbial informatics
- Microbiome
- Phylogenetic tree
ASJC Scopus subject areas
- Biotechnology
- Structural Biology
- Biophysics
- Biochemistry
- Genetics
- Computer Science Applications
Cite this
SigTree : A Microbial Community Analysis Tool to Identify and Visualize Significantly Responsive Branches in a Phylogenetic Tree. / Stevens, John R.; Jones, Todd R.; Lefevre, Michael; Ganesan, Balasubramanian; Weimer, Bart C.
In: Computational and Structural Biotechnology Journal, Vol. 15, 2017, p. 372-378.Research output: Contribution to journal › Short survey
}
TY - JOUR
T1 - SigTree
T2 - A Microbial Community Analysis Tool to Identify and Visualize Significantly Responsive Branches in a Phylogenetic Tree
AU - Stevens, John R.
AU - Jones, Todd R.
AU - Lefevre, Michael
AU - Ganesan, Balasubramanian
AU - Weimer, Bart C
PY - 2017
Y1 - 2017
N2 - Microbial community analysis experiments to assess the effect of a treatment intervention (or environmental change) on the relative abundance levels of multiple related microbial species (or operational taxonomic units) simultaneously using high throughput genomics are becoming increasingly common. Within the framework of the evolutionary phylogeny of all species considered in the experiment, this translates to a statistical need to identify the phylogenetic branches that exhibit a significant consensus response (in terms of operational taxonomic unit abundance) to the intervention. We present the R software package SigTree, a collection of flexible tools that make use of meta-analysis methods and regular expressions to identify and visualize significantly responsive branches in a phylogenetic tree, while appropriately adjusting for multiple comparisons.
AB - Microbial community analysis experiments to assess the effect of a treatment intervention (or environmental change) on the relative abundance levels of multiple related microbial species (or operational taxonomic units) simultaneously using high throughput genomics are becoming increasingly common. Within the framework of the evolutionary phylogeny of all species considered in the experiment, this translates to a statistical need to identify the phylogenetic branches that exhibit a significant consensus response (in terms of operational taxonomic unit abundance) to the intervention. We present the R software package SigTree, a collection of flexible tools that make use of meta-analysis methods and regular expressions to identify and visualize significantly responsive branches in a phylogenetic tree, while appropriately adjusting for multiple comparisons.
KW - Microbial community analysis
KW - Microbial informatics
KW - Microbiome
KW - Phylogenetic tree
UR - http://www.scopus.com/inward/record.url?scp=85024133187&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85024133187&partnerID=8YFLogxK
U2 - 10.1016/j.csbj.2017.06.002
DO - 10.1016/j.csbj.2017.06.002
M3 - Short survey
AN - SCOPUS:85024133187
VL - 15
SP - 372
EP - 378
JO - Computational and Structural Biotechnology Journal
JF - Computational and Structural Biotechnology Journal
SN - 2001-0370
ER -