Demo Data from EDBT 2026 / reviewers in the wild / expert
Stephen J. Finch
dblp:96/2652
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › statistical genetics
genetic association study |
0.1 | 1 | 2005 | PAWE-3D: visualizing power for association with error in case-control genetic studies of complex traits · Bioinform. 2005 |
Bioinformatics and computational biology › biostatistics
sample size determination |
0.1 | 1 | 2005 | PAWE-3D: visualizing power for association with error in case-control genetic studies of complex traits · Bioinform. 2005 |
Bioinformatics and computational biology
case-control study |
0.0 | 1 | 2005 | PAWE-3D: visualizing power for association with error in case-control genetic studies of complex traits · Bioinform. 2005 |
Methods — techniques the papers use, named apart from their topics
linear trend test · 0.1genotypic test of association · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | TDT-HET: A new transmission disequilibrium test that incorporates locus heterogeneity into the analysis of family-based association dataabstractBACKGROUND: Locus heterogeneity is one of the most documented phenomena in genetics. To date, relatively little work had been done on the development of methods to address locus heterogeneity in genetic association analysis. Motivated by Zhou and Pan's work, we present a mixture model of linked and unlinked trios and develop a statistical method to estimate the probability that a heterozygous parent transmits the disease allele at a di-allelic locus, and the probability that any trio is in the linked group. The purpose here is the development of a test that extends the classic transmission disequilibrium test (TDT) to one that accounts for locus heterogeneity. RESULTS: Our simulations suggest that, for sufficiently large sample size (1000 trios) our method has good power to detect association even the proportion of unlinked trios is high (75%). While the median difference (TDT-HET empirical power - TDT empirical power) is approximately 0 for all MOI, there are parameter settings for which the power difference can be substantial. Our multi-locus simulations suggest that our method has good power to detect association as long as the markers are reasonably well-correlated and the genotype relative risk are larger. Results of both single-locus and multi-locus simulations suggest our method maintains the correct type I error rate.Finally, the TDT-HET statistic shows highly significant p-values for most of the idiopathic scoliosis candidate loci, and for some loci, the estimated proportion of unlinked trios approaches or exceeds 50%, suggesting the presence of locus heterogeneity. CONCLUSIONS: We have developed an extension of the TDT statistic (TDT-HET) that allows for locus heterogeneity among coded trios. Benefits of our method include: estimates of parameters in the presence of heterogeneity, and reasonable power even when the proportion of linked trios is small. Also, we have extended multi-locus methods to TDT-HET and have demonstrated that the empirical power may be high to detect linkage. Last, given that we obtain PPBs, we conjecture that the TDT-HET may be a useful method for correctly identifying linked trios. We anticipate that researchers will find this property increasingly useful as they apply next-generation sequencing data in family based studies. Douglas Londono, Steven Buyske, Stephen J. Finch, Swarkar Sharma, Carol A. Wise, Derek Gordon |
BMC Bioinform. | 3 |
| 2005 | PAWE-3D: visualizing power for association with error in case-control genetic studies of complex traitsabstractUNLABELLED: A website that plots power and sample size calculations over a range of up to eight parameters (including diagnostic misclassification error parameters) for two commonly used statistical tests of genetic association, the linear trend test and the genotypic test of association. AVAILABILITY: This method is made available via the website http://linkage.rockefeller.edu/pawe3d/ CONTACT: [email protected]. Derek Gordon, Chad Haynes, Jon Blumenfeld, Stephen J. Finch |
Bioinform. | 4 |