SynthesisJournal of human genetics2008
CHROMSCAN: genome-wide association using a linkage disequilibrium map.
Synthesis in Journal of human genetics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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Who cites it
4 citing papers in PubMed.
- Linkage disequilibrium maps for European and African populations constructed from whole genome sequence data.Scientific data · 2019Article
- Genome-wide association of breast cancer: composite likelihood with imputed genotypes.European journal of human genetics : EJHG · 2011Article
- Phase uncertainty in case-control association studies.Genetic epidemiology · 2009Article
- Allelic association: linkage disequilibrium structure and gene mapping.Molecular biotechnology · 2009Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
CHROMSCAN implements a composite likelihood model for the analysis of association data. Disease-gene localisation is on a linkage disequilibrium unit (LDU) map, and locations and standard errors, for putatively causal polymorphisms, are determined by the programme. Distortions of the probability distribution created by auto-correlation are avoided by implementation of a permutation test. We evaluated the relative efficiency of the LDU map by simulating pseudo-phenotypes in real genotype samples. We observed that multi-locus mapping on an underlying LDU map reduces location error by approximately 46%. Furthermore, there is a small, but significant, increase in power of approximately 5%. Effective meta-analysis across multiple samples, increasingly important to combine evidence from genome-wide and other association data, is achieved through the weighted combination of location evidence provided by the programme.
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Identifiers
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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.