Evidence map›Paper›PMID 28449263›Full record

ArticleMolecular ecology resources2017

multi-dice: r package for comparative population genomic inference under hierarchical co-demographic models of independent single-population size changes.

Alexander T Xue, Michael J Hickerson

Abstract read
In one paragraph

Article in Molecular ecology resources, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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  4. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Alexander T XueDepartment of Biology: Subprogram in Ecology, Evolutionary Biology, and Behavior, City College and Graduate Center of City University of New York, New York, NY, USA.ORCID http://orcid.org/0000-0003-1521-6448
Michael J HickersonDepartment of Biology: Subprogram in Ecology, Evolutionary Biology, and Behavior, City College and Graduate Center of City University of New York, New York, NY, USA.

Funding

Population Genomics of LINE Retrotransposons in VertebratesR15GM096267 · NIGMS · QUEENS COLLEGE · PI BOISSINOT, STEPHANE · 2011 to 2011
$303k
NIGMS NIH HHS R15 GM096267
6 · The paper itself

Abstract

Population genetic data from multiple taxa can address comparative phylogeographic questions about community-scale response to environmental shifts, and a useful strategy to this end is to employ hierarchical co-demographic models that directly test multi-taxa hypotheses within a single, unified analysis. This approach has been applied to classical phylogeographic data sets such as mitochondrial barcodes as well as reduced-genome polymorphism data sets that can yield 10,000s of SNPs, produced by emergent technologies such as RAD-seq and GBS. A strategy for the latter had been accomplished by adapting the site frequency spectrum to a novel summarization of population genomic data across multiple taxa called the aggregate site frequency spectrum (aSFS), which potentially can be deployed under various inferential frameworks including approximate Bayesian computation, random forest and composite likelihood optimization. Here, we introduce the r package multi-dice, a wrapper program that exploits existing simulation software for flexible execution of hierarchical model-based inference using the aSFS, which is derived from reduced genome data, as well as mitochondrial data. We validate several novel software features such as applying alternative inferential frameworks, enforcing a minimal threshold of time surrounding co-demographic pulses and specifying flexible hyperprior distributions. In sum, multi-dice provides comparative analysis within the familiar R environment while allowing a high degree of user customization, and will thus serve as a tool for comparative phylogeography and population genomics.

Indexed as

MetagenomicsPopulation DensitySoftwareBiostatisticsaggregate site frequency spectrumapproximate Bayesian computationcomparative phylogeographypopulation genetics softwarerandom forest

Identifiers

PMID28449263
PMCPMC5724483

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.