Correcting bias in allele frequency estimates to an observation threshold: A Markov chain analysis

Goßmann T, Waxman D (Accepted)
Genome Biology and Evolution.

Zeitschriftenaufsatz | Angenommen | Englisch
 
Download
OA 4.36 MB
Autor*in
Goßmann, ToniUniBi ; Waxman, David
Abstract / Bemerkung
There are many problems in biology and related disciplines involving stochasticity, where a signal can only be detected when it lies above a threshold level, while signals lying below threshold are simply not detected. A consequence is that the detected signal is conditioned to lie above threshold, and is not representative of the actual signal. In this work we present some general results for the conditioning that occurs due to the existence of such an observational threshold. We show that this conditioning is relevant, for example, to gene-frequency trajectories, where many loci in the genome are simultaneously measured in a given generation. Such a threshold can lead to severe biases of allele frequency estimates under purifying selection. In the analysis presented, within the context of Markov chains such as the Wright-Fisher model, we address two key questions: (1) `What is a natural measure of the strength of the conditioning associated with an observation threshold?' (2) `What is a principled way to correct for the effects of the conditioning?'. We answer the first question in terms of a proportion. Starting with a large number of trajectories, the relevant quantity is the proportion of these trajectories that are above threshold at a later time and hence are detected. The smaller the value of this proportion, the stronger the effects of conditioning. We provide an approximate analytical answer to the second question, that corrects the bias produced by an observation threshold, and performs to reasonable accuracy in the Wright-Fisher model for biologically plausible parameter values.
Erscheinungsjahr
2022
Zeitschriftentitel
Genome Biology and Evolution
eISSN
1759-6653
Finanzierungs-Informationen
Open-Access-Publikationskosten wurden durch die Universität Bielefeld gefördert.
Page URI
https://pub.uni-bielefeld.de/record/2962125

Zitieren

Goßmann T, Waxman D. Correcting bias in allele frequency estimates to an observation threshold: A Markov chain analysis. Genome Biology and Evolution. Accepted.
Goßmann, T., & Waxman, D. (Accepted). Correcting bias in allele frequency estimates to an observation threshold: A Markov chain analysis. Genome Biology and Evolution. https://doi.org/10.1093/gbe/evac047
Goßmann, Toni, and Waxman, David. Accepted. “Correcting bias in allele frequency estimates to an observation threshold: A Markov chain analysis”. Genome Biology and Evolution.
Goßmann, T., and Waxman, D. (Accepted). Correcting bias in allele frequency estimates to an observation threshold: A Markov chain analysis. Genome Biology and Evolution.
Goßmann, T., & Waxman, D., Accepted. Correcting bias in allele frequency estimates to an observation threshold: A Markov chain analysis. Genome Biology and Evolution.
T. Goßmann and D. Waxman, “Correcting bias in allele frequency estimates to an observation threshold: A Markov chain analysis”, Genome Biology and Evolution, Accepted.
Goßmann, T., Waxman, D.: Correcting bias in allele frequency estimates to an observation threshold: A Markov chain analysis. Genome Biology and Evolution. (Accepted).
Goßmann, Toni, and Waxman, David. “Correcting bias in allele frequency estimates to an observation threshold: A Markov chain analysis”. Genome Biology and Evolution (Accepted).
Alle Dateien verfügbar unter der/den folgenden Lizenz(en):
Creative Commons Namensnennung-Nicht kommerziell 4.0 International (CC BY-NC 4.0):
Volltext(e)
Name
Access Level
OA Open Access
Zuletzt Hochgeladen
2022-04-05T13:22:21Z
MD5 Prüfsumme
7f3f72d85eb38ab99508d354c928ced4


Link(s) zu Volltext(en)
Access Level
OA Open Access

Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

References

Daten bereitgestellt von Europe PubMed Central.

Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®
Quellen

PMID: 35349695
PubMed | Europe PMC

Suchen in

Google Scholar