Power and sample size calculations for testing the ratio of reproductive values in phylogenetic samples

The quality of the inferences we make from pathogen sequence data is determined by the number and composition of pathogen sequences that make up the sample used to drive that inference. However, there remains limited guidance on how to best structure and power studies when the end goal is phylogenetic inference. One question that we can attempt to answer with molecular data is whether some people are more likely to transmit a pathogen than others. Here we present an estimator to quantify differential transmission, as measured by the ratio of reproductive numbers between people with different characteristics, using transmission pairs linked by molecular data, along with a sample size calculation for this estimator. We also provide extensions to our method to correct for imperfect identification of transmission-linked pairs, overdispersion in the transmission process, and group imbalance. We validate this method via simulation and provide tools to implement it in an R package, phylosamp.

Authors

Institutions

Publication Details

Journal
American Journal of Epidemiology
Published
2024-10-10
DOI
https://doi.org/10.1093/aje/kwae378
Citations
1
Primary Topic
Gut microbiota and health
Type
article
Field-Weighted Citation Impact
0.23
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Power and sample size calculations for testing the ratio of reproductive values in phylogenetic samples

Justin Lessler, Shirlee Wohl, Lucy D’Agostino McGowan
1 citations
American Journal of Epidemiology
Gut microbiota and health
0.23
article

Power and sample size calculations for testing the ratio of reproductive values in phylogenetic samples

Justin Lessler, Shirlee Wohl, Lucy D’Agostino McGowan
article en
1 citations

Abstract

The quality of the inferences we make from pathogen sequence data is determined by the number and composition of pathogen sequences that make up the sample used to drive that inference. However, there remains limited guidance on how to best structure and power studies when the end goal is phylogenetic inference. One question that we can attempt to answer with molecular data is whether some people are more likely to transmit a pathogen than others. Here we present an estimator to quantify differential transmission, as measured by the ratio of reproductive numbers between people with different characteristics, using transmission pairs linked by molecular data, along with a sample size calculation for this estimator. We also provide extensions to our method to correct for imperfect identification of transmission-linked pairs, overdispersion in the transmission process, and group imbalance. We validate this method via simulation and provide tools to implement it in an R package, phylosamp.

American Journal of EpidemiologyVol. 194(8)
University of North Carolina at Chapel Hill (US), Scripps Research Institute (US), Johns Hopkins University (US), Wake Forest University (US)
Openalex Percentile: Top 42%
Gut microbiota and health
0.23
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Power and sample size calculations for testing the ratio of reproductive values in phylogenetic samples — Justin Lessler, Shirlee Wohl, et al. · American Journal of Epidemiology (2024) | TGRS Research Map | TGRS