Evidence map›Paper›PMID 27408750›Full record

ArticleHuman genome variation2016

The Qatar genome: a population-specific tool for precision medicine in the Middle East.

Khalid A Fakhro, Michelle R Staudt, Monica Denise Ramstetter, Amal Robay, Joel A Malek, Ramin Badii, Ajayeb Al-Nabet Al-Marri, Charbel Abi Khalil, Alya Al-Shakaki, Omar Chidiac and 7 more

Abstract read
In one paragraph

Article in Human genome variation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
83citing papers in PubMed, 2 pooled it
–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

83 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  7. Reclassification ofBiomolecules & biomedicine · 2026
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  12. FivePharmacogenomics and personalized medicine · 2026
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23 more citing papers are in PubMed but not listed here.

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

17 authors.

Khalid A FakhroSidra Medical and Research Center, Doha, Qatar; Department of Genetic Medicine, Weill Cornell Medical College in Qatar, Doha, Qatar.
Michelle R StaudtDepartment of Genetic Medicine, Weill Cornell Medical College , New York, NY, USA.
Monica Denise RamstetterDepartment of Genetic Medicine, Weill Cornell Medical College , New York, NY, USA.
Amal RobayDepartment of Genetic Medicine, Weill Cornell Medical College in Qatar , Doha, Qatar.
Joel A MalekDepartment of Genetic Medicine, Weill Cornell Medical College in Qatar , Doha, Qatar.
Ramin BadiiLaboratory Medicine and Pathology, Hamad Medical Corporation , Doha, Qatar.
Ajayeb Al-Nabet Al-MarriLaboratory Medicine and Pathology, Hamad Medical Corporation , Doha, Qatar.
Charbel Abi KhalilDepartment of Genetic Medicine, Weill Cornell Medical College in Qatar , Doha, Qatar.
Alya Al-ShakakiDepartment of Genetic Medicine, Weill Cornell Medical College in Qatar , Doha, Qatar.
Omar ChidiacDepartment of Genetic Medicine, Weill Cornell Medical College in Qatar , Doha, Qatar.
Dora StadlerWeill Cornell Medical College in Qatar , Doha, Qatar.
Mahmoud ZirieDepartment of Medicine, Hamad Medical Corporation , Doha, Qatar.
Amin JayyousiDepartment of Medicine, Hamad Medical Corporation , Doha, Qatar.
Jacqueline SalitDepartment of Genetic Medicine, Weill Cornell Medical College , New York, NY, USA.
Jason G MezeyDepartment of Genetic Medicine, Weill Cornell Medical College, New York, NY, USA; Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, USA.
Ronald G CrystalDepartment of Genetic Medicine, Weill Cornell Medical College , New York, NY, USA.
Juan L Rodriguez-FloresDepartment of Genetic Medicine, Weill Cornell Medical College , New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reaching the full potential of precision medicine depends on the quality of personalized genome interpretation. In order to facilitate precision medicine in regions of the Middle East and North Africa (MENA), a population-specific genome for the indigenous Arab population of Qatar (QTRG) was constructed by incorporating allele frequency data from sequencing of 1,161 Qataris, representing 0.4% of the population. A total of 20.9 million single nucleotide polymorphisms (SNPs) and 3.1 million indels were observed in Qatar, including an average of 1.79% novel variants per individual genome. Replacement of the GRCh37 standard reference with QTRG in a best practices genome analysis workflow resulted in an average of 7* deeper coverage depth (an improvement of 23%) and 756,671 fewer variants on average, a reduction of 16% that is attributed to common Qatari alleles being present in QTRG. The benefit for using QTRG varies across ancestries, a factor that should be taken into consideration when selecting an appropriate reference for analysis.

Identifiers

PMID27408750
PMCPMC4927697

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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.