Evidence map›Paper›PMID 17709344›Full record

ArticleNucleic acids research2007

A systematic strategy for large-scale analysis of genotype phenotype correlations: identification of candidate genes involved in African trypanosomiasis.

Paul Fisher, Cornelia Hedeler, Katherine Wolstencroft, Helen Hulme, Harry Noyes, Stephen Kemp, Robert Stevens, Andrew Brass

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Nucleic acids research, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
6.9field-weighted citation impact, top 3% 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

20 citing papers in PubMed, 60 citations in OpenAlex.

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  7. QTL/microarray approach using pathway information.Algorithms for molecular biology : AMB · 2012
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  8. Genetic and expression analysis of cattle identifies candidate genes in pathways responding to Trypanosoma congolense infection.Proceedings of the National Academy of Sciences of the United States of America · 2011
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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

8 authors at 2 institutions in 1 country.

Paul FisherSchool of Computer Science, Kilburn Building, University of Manchester, Oxford Road, Manchester, UK. pfisher@cs.manchester.ac.uk
Cornelia Hedeler
Katherine Wolstencroft
Helen Hulme
Harry Noyes
Stephen Kemp
Robert Stevens
Andrew Brass
University of Liverpool · GBUniversity of Manchester · GB

Funding

Wellcome Trust GR066764MA
6 · The paper itself

Abstract

It is increasingly common to combine Microarray and Quantitative Trait Loci data to aid the search for candidate genes responsible for phenotypic variation. Workflows provide a means of systematically processing these large datasets and also represent a framework for the re-use and the explicit declaration of experimental methods. In this article, we highlight the issues facing the manual analysis of microarray and QTL data for the discovery of candidate genes underlying complex phenotypes. We show how automated approaches provide a systematic means to investigate genotype-phenotype correlations. This methodology was applied to a use case of resistance to African trypanosomiasis in the mouse. Pathways represented in the results identified Daxx as one of the candidate genes within the Tir1 QTL region. Subsequent re-sequencing in Daxx identified a deletion of an amino acid, identified in susceptible mouse strains, in the Daxx-p53 protein-binding region. This supports recent experimental evidence that apoptosis could be playing a role in the trypanosomiasis resistance phenotype. Workflows developed in this investigation, including a guide to loading and executing them with example data, are available at http://workflows.mygrid.org.uk/repository/myGrid/PaulFisher/.

Indexed as

Gene Expression ProfilingGenetic Predisposition to DiseaseQuantitative Trait LociAnimalsBase SequenceCarrier ProteinsCo-Repressor ProteinsGenotypeImmunity, InnateIntracellular Signaling Peptides and ProteinsMiceMolecular ChaperonesMolecular Sequence DataNuclear ProteinsOligonucleotide Array Sequence AnalysisPhenotypeCarrier ProteinsCo-Repressor ProteinsDaxx protein, mouseIntracellular Signaling Peptides and ProteinsMolecular ChaperonesNuclear Proteins

Identifiers

PMID17709344
PMCPMC2018629
OpenAlexW2156222477

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.