ArticleGenetic epidemiology2012
Optimized selection of unrelated subjects for whole-genome sequencing studies of rare high-penetrance alleles.
Article in Genetic epidemiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Kinship Decouple and Phenotype Selection (KDPS): a tool for phenotype-aware decoupling of related subjects.Briefings in bioinformatics · 2025Article
- Increased prevalence of EPAS1 variant in cattle with high-altitude pulmonary hypertension.Nature communications · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Sequencing studies using whole-genome or exome scans are still more expensive than genome-wide association studies on a per-subject basis. As a result, only a subset of subjects from a larger study will be selected for sequencing. To perform an agnostic investigation of the entire genome, subjects may be selected that capture independent ancestral lineages, i.e., founder genomes, and thus avoid redundant information from regions that were inherited identical by descent (IBD) from a common ancestor. We present SampleSeq2 that can be used to select a subset of optimally unrelated subjects with minimal IBD sharing. It also can be used to estimate the number, G(T), of founder chromosomes in a sample or select the minimum number of subjects that will carry a target G(T). We evaluated SampleSeq2 compared to a random draw of a small number of subjects both by simulation and using the Anabaptist genealogy. SampleSeq2 provided an increase in G(T) relative to a random draw across a range of small sample sizes. This increase in founder chromosomes improves the power of association tests, mitigates the effect of cryptic relatedness on parameter estimates, increases the total yield of alleles from sequencing, and minimizes the average size of regions shared IBD around disease alleles in cases.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.