Evidence map›Paper›PMID 37532769›Full record

ArticleCommunications biology2023

Direct inference and control of genetic population structure from RNA sequencing data.

Muhamad Fachrul, Abhilasha Karkey, Mila Shakya, Louise M Judd, Taylor Harshegyi, Kar Seng Sim, Susan Tonks, Sabina Dongol, Rajendra Shrestha, Agus Salim and 9 more

Abstract read
In one paragraph

Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Genotype prediction of 336,463 samples from public expression data.bioRxiv : the preprint server for biology · 2024
    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

19 authors.

Muhamad FachrulCambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia. fachrul.mhmd@gmail.com.ORCID 0000-0003-2199-5900
Abhilasha KarkeyOxford University Clinical Research Unit, Patan Academy of Health Sciences, Kathmandu, Nepal.
Mila ShakyaOxford University Clinical Research Unit, Patan Academy of Health Sciences, Kathmandu, Nepal.
Louise M JuddDepartment of Infectious Diseases, Central Clinical School, Monash University, Melbourne, VIC, Australia.
Taylor HarshegyiDepartment of Infectious Diseases, Central Clinical School, Monash University, Melbourne, VIC, Australia.ORCID 0000-0001-9620-8735
Kar Seng SimGenome Institute of Singapore, Singapore, Singapore.
Susan TonksOxford Vaccine Group, Department of Paediatrics, University of Oxford, and the NIHR Oxford Biomedical Research Centre, Oxford, UK.
Sabina DongolOxford University Clinical Research Unit, Patan Academy of Health Sciences, Kathmandu, Nepal.
Rajendra ShresthaPatan Academy of Health Sciences, Patan Hospital, Lalitpur, Nepal.
Agus SalimCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
STRATAA study group
Stephen BakerDepartment of Medicine, University of Cambridge, Cambridge, UK.
Andrew J PollardOxford Vaccine Group, Department of Paediatrics, University of Oxford, and the NIHR Oxford Biomedical Research Centre, Oxford, UK.ORCID 0000-0001-7361-719X
Chiea Chuen KhorGenome Institute of Singapore, Singapore, Singapore.ORCID 0000-0002-1128-4729
Christiane DolecekNuffield Department of Medicine, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK.
Buddha BasnyatOxford University Clinical Research Unit, Patan Academy of Health Sciences, Kathmandu, Nepal.
Sarah J DunstanThe Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, VIC, Australia.ORCID 0000-0001-7873-933X
Kathryn E HoltDepartment of Infectious Diseases, Central Clinical School, Monash University, Melbourne, VIC, Australia.ORCID 0000-0003-3949-2471
Michael InouyeCambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia. mi336@medschl.cam.ac.uk.ORCID 0000-0001-9413-6520

Funding

British Heart Foundation RG/18/13/33946Department of Health BRC-1215-20014Department of Health NIHR203312Medical Research CouncilWellcome TrustWellcome Trust 106158/Z/14/Z
6 · The paper itself

Abstract

RNAseq data can be used to infer genetic variants, yet its use for estimating genetic population structure remains underexplored. Here, we construct a freely available computational tool (RGStraP) to estimate RNAseq-based genetic principal components (RG-PCs) and assess whether RG-PCs can be used to control for population structure in gene expression analyses. Using whole blood samples from understudied Nepalese populations and the Geuvadis study, we show that RG-PCs had comparable results to paired array-based genotypes, with high genotype concordance and high correlations of genetic principal components, capturing subpopulations within the dataset. In differential gene expression analysis, we found that inclusion of RG-PCs as covariates reduced test statistic inflation. Our paper demonstrates that genetic population structure can be directly inferred and controlled for using RNAseq data, thus facilitating improved retrospective and future analyses of transcriptomic data.

Indexed as

Genetics, PopulationBase SequenceGenotypeHumansRetrospective StudiesSequence Analysis, RNA

Identifiers

PMID37532769
PMCPMC10397182

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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.