Evidence map›Paper›PMID 23290073›Full record

ArticleAmerican journal of human genetics2013

Deep whole-genome sequencing of 100 southeast Asian Malays.

Lai-Ping Wong, Rick Twee-Hee Ong, Wan-Ting Poh, Xuanyao Liu, Peng Chen, Ruoying Li, Kevin Koi-Yau Lam, Nisha Esakimuthu Pillai, Kar-Seng Sim, Haiyan Xu and 20 more

Abstract read
In one paragraph

Article in American journal of human genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
106citing 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

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

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46 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

30 authors.

Lai-Ping WongSaw Swee Hock School of Public Health, National University of Singapore, Singapore 117597, Singapore.
Rick Twee-Hee Ong
Wan-Ting Poh
Xuanyao Liu
Peng Chen
Ruoying Li
Kevin Koi-Yau Lam
Nisha Esakimuthu Pillai
Kar-Seng Sim
Haiyan Xu
Ngak-Leng Sim
Shu-Mei Teo
Jia-Nee Foo
Linda Wei-Lin Tan
Yenly Lim
Seok-Hwee Koo
Linda Seo-Hwee Gan
Ching-Yu Cheng
Sharon Wee
Eric Peng-Huat Yap
Pauline Crystal Ng
Wei-Yen Lim
Richie Soong
Markus Rene Wenk
Tin Aung
Tien-Yin Wong
Chiea-Chuen Khor
Peter Little
Kee-Seng Chia
Yik-Ying Teo

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Whole-genome sequencing across multiple samples in a population provides an unprecedented opportunity for comprehensively characterizing the polymorphic variants in the population. Although the 1000 Genomes Project (1KGP) has offered brief insights into the value of population-level sequencing, the low coverage has compromised the ability to confidently detect rare and low-frequency variants. In addition, the composition of populations in the 1KGP is not complete, despite the fact that the study design has been extended to more than 2,500 samples from more than 20 population groups. The Malays are one of the Austronesian groups predominantly present in Southeast Asia and Oceania, and the Singapore Sequencing Malay Project (SSMP) aims to perform deep whole-genome sequencing of 100 healthy Malays. By sequencing at a minimum of 30× coverage, we have illustrated the higher sensitivity at detecting low-frequency and rare variants and the ability to investigate the presence of hotspots of functional mutations. Compared to the low-pass sequencing in the 1KGP, the deeper coverage allows more functional variants to be identified for each person. A comparison of the fidelity of genotype imputation of Malays indicated that a population-specific reference panel, such as the SSMP, outperforms a cosmopolitan panel with larger number of individuals for common SNPs. For lower-frequency (<5%) markers, a larger number of individuals might have to be whole-genome sequenced so that the accuracy currently afforded by the 1KGP can be achieved. The SSMP data are expected to be the benchmark for evaluating the value of deep population-level sequencing versus low-pass sequencing, especially in populations that are poorly represented in population-genetics studies.

Indexed as

Genetic VariationHigh-Throughput Nucleotide SequencingAsian PeopleGenetics, PopulationGenome, HumanHumansMalaysiaPolymorphism, Single NucleotidePopulation GroupsSingapore

Identifiers

PMID23290073
PMCPMC3542459

What OpenQuestion holds

Textmetadata
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.