Evidence map›Paper›PMID 22537047›Full record

ArticleBMC bioinformatics2012

High-resolution genetic mapping with pooled sequencing.

Matthew D Edwards, David K Gifford

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

36 citing papers in PubMed, 76 citations in OpenAlex.

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  10. Restoring fertility in yeast hybrids: Breeding and quantitative genetics of beneficial traits.Proceedings of the National Academy of Sciences of the United States of America · 2021
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  18. Genome-Wide Screen forG3 (Bethesda, Md.) · 2018
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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 2 institutions in 1 country.

Matthew D EdwardsComputer Science and Artificial Intelligence Laboratory, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
David K Gifford
Massachusetts Institute of Technology · USWhitehead Institute for Biomedical Research · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundModern genetics has been transformed by high-throughput sequencing. New experimental designs in model organisms involve analyzing many individuals, pooled and sequenced in groups for increased efficiency. However, the uncertainty from pooling and the challenge of noisy sequencing data demand advanced computational methods.

resultsWe present MULTIPOOL, a computational method for genetic mapping in model organism crosses that are analyzed by pooled genotyping. Unlike other methods for the analysis of pooled sequence data, we simultaneously consider information from all linked chromosomal markers when estimating the location of a causal variant. Our use of informative sequencing reads is formulated as a discrete dynamic Bayesian network, which we extend with a continuous approximation that allows for rapid inference without a dependence on the pool size. MULTIPOOL generalizes to include biological replicates and case-only or case-control designs for binary and quantitative traits.

conclusionsOur increased information sharing and principled inclusion of relevant error sources improve resolution and accuracy when compared to existing methods, localizing associations to single genes in several cases. MULTIPOOL is freely available at http://cgs.csail.mit.edu/multipool/.

Indexed as

Chromosome MappingGene FrequencyAnimalsBayes TheoremCase-Control StudiesGenetic MarkersGenotypeHumansModels, AnimalModels, StatisticalMultilocus Sequence TypingPhenotypePolymorphism, Single NucleotideGenetic Markers

Identifiers

PMID22537047
PMCPMC3358661
OpenAlexW2128913537

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.