Evidence map›Paper›PMID 22373232›Full record

ArticleBMC proceedings2011

Strategies for selection of subjects for sequencing after detection of a linkage peak.

Kristina Allen-Brady, James Farnham, Lisa Cannon-Albright

Abstract read
In one paragraph

Article in BMC proceedings, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

3 authors.

Kristina Allen-BradyDivision of Genetic Epidemiology, Department of Internal Medicine, University of Utah, 391 Chipeta Way, Suite D, Salt Lake City, UT 84105, USA.
James FarnhamDivision of Genetic Epidemiology, Department of Internal Medicine, University of Utah, 391 Chipeta Way, Suite D, Salt Lake City, UT 84105, USA.
Lisa Cannon-AlbrightDivision of Genetic Epidemiology, Department of Internal Medicine, University of Utah, 391 Chipeta Way, Suite D, Salt Lake City, UT 84105, USA ; George E. Wallen Department of Veterans Affairs Medical Center, 500 Foothill Drive, Salt Lake City, UT 84148, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Linkage analysis has the potential to localize disease genes of interest, but the choice of which subjects to select for follow-up sequencing after identifying a linkage peak might influence the ability to find a disease gene. We compare nine different strategies for selection of subjects for follow-up sequencing using sequence data from the Genetic Analysis Workshop 17. We found that our more selective strategies, which included methods to identify case subjects more likely to be affected by genetic causes, out-performed sequencing all case and control subjects in linked pedigrees and required sequencing fewer individuals. We found that using genotype data from population control subjects had a higher benefit-cost ratio than sequencing control subjects selected as being the opposite extreme of the case subjects. We conclude that choosing case subjects for sequencing based on more selective strategies can be reliable and cost-effective.

Identifiers

PMID22373232
PMCPMC3287917

What OpenQuestion holds

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Registered trials

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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.