Evidence map›Paper›PMID 16451630›Full record

ArticleBMC genetics2005

Interval estimation of disease loci: development and applications of new linkage methods.

Charalampos Papachristou, Shili Lin

Open access · diamondAbstract read
In one paragraph

Article in BMC genetics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 39% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Charalampos PapachristouDepartment of Statistics, The Ohio State University, 1958 Neil Avenue, Columbus, OH 43210, USA. babis@stat.ohio-state.edu
Shili Lin
The Ohio State University · US

Funding

Statistical Methods for Gene Mapping: a New ParadigmR01HG002657 · NHGRI · OHIO STATE UNIVERSITY · PI LIN, SHILI · 2004 to 2006
$439k
NHGRI NIH HHS 1R01HG002657-01A1NHGRI NIH HHS R01 HG002657
6 · The paper itself

Abstract

Three variants of the confidence set inference (CSI) procedure were proposed and applied to both the simulated and the Collaborative Study on the Genetics of Alcoholism (COGA) data. For each of the two applications, we first performed a preliminary genome scan study based on the microsatellite markers using the GENEHUNTER+ software to identify regions that potentially harbor disease loci. For each such region, we estimated the sibling identity-by-descent sharing probability distribution at the putative disease locus. Based on these estimated probabilities, the CSI procedures were employed to further localize the disease loci using the single-nucleotide polymorphism markers, leading to confidence intervals/regions for their locations. For our analysis with the simulated data, we had knowledge of the simulating models at the time we performed the analysis.

Indexed as

AlcoholismChromosome MappingComputer SimulationCooperative BehaviorDatabases, GeneticDiseaseGenetic LociHumans

Identifiers

PMID16451630
PMCPMC1866765
OpenAlexW2142561698

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.