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Estimating Effective Population Size or Mutation Rate with Microsatellites

*Corresponding author for this work
  • University of Texas Health Science Center at Houston
Scholary Output:
Contribution to journal
Article
Research
Peer-review

Open access

Abstract

Microsatellites are short tandem repeats that are widely dispersed among eukaryotic genomes. Many of them are highly polymorphic; they have been used widely in genetic studies. Statistical properties of all measures of genetic variation at microsatellites critically depend upon the composite parameter θ = 4Nμ, where N is the effective population size and μ is mutation rate per locus per generation. Since mutation leads to expansion or contraction of a repeat number in a stepwise fashion, the stepwise mutation model has been widely used to study the dynamics of these loci. We developed an estimator of θ, θF, on the basis of sample homozygosity under the single-step stepwise mutation model. The estimator is unbiased and is much more efficient than the variance-based estimator under the single-step stepwise mutation model. It also has smaller bias and mean square error (MSE) than the variance-based estimator when the mutation follows the multistep generalized stepwise mutation model. Compared with the maximum-likelihood estimator θL by NIELSEN (1997), θF has less bias and smaller MSE in general. θL has a slight advantage when θ is small, but in such a situation the bias in θL may be more of a concern.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Research
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 555-563 (9 pages)

Journal (Volume, Issue Number)

Genetics (Volume 166, Issue 1)

Publication milestones

  • Published - 01/2004

Publication status

Published - 01/2004

ISSN

0016-6731

Publication IDs

  • Scopus: 1642337411
  • PubMed: 15020444

Publication metrics

Metrics

SciVal
citations
46
Scopus
citations
Fractional count
1
Fractional count
0.50
Fractional count
1
Fractional count
0.50
Fractional count
1
Fractional count
1
SciVal
FWCI
1.20
SciVal
Author count
2
SciVal
Paper percentile
85

PlumX, opens in new tab

Citation count
54
Captures
150

Funding Details

FunderFunding number
NIGMS
R01GM050428