Evidence map›Paper›PMID 34099647›Full record

ArticleNature communications2021

Replicate sequencing libraries are important for quantification of allelic imbalance.

Asia Mendelevich, Svetlana Vinogradova, Saumya Gupta, Andrey A Mironov, Shamil R Sunyaev, Alexander A Gimelbrant

Abstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Mechanisms of transcriptional regulation inProceedings. Biological sciences · 2024
    Article
  8. Article
  9. Article
  10. Mechanisms of transcriptional regulation inbioRxiv : the preprint server for biology · 2023
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Frontiers in cell and developmental biology · 2022
    Article
  17. 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

6 authors.

Asia Mendelevich *Skolkovo Institute of Science and Technology, Moscow, Russia. a.mendelevich@skoltech.ru.ORCID http://orcid.org/0000-0002-1221-3287
Svetlana Vinogradova *Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, USA.ORCID http://orcid.org/0000-0002-5419-8812
Saumya GuptaCenter for Cancer Systems Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, USA.ORCID http://orcid.org/0000-0001-7703-918X
Andrey A MironovLomonosov Moscow State University, Faculty of Bioengineering and Bioinformatics, Moscow, Russia.
Shamil R SunyaevDepartment of Biomedical Informatics, Harvard Medical School, Boston, USA.
Alexander A GimelbrantCenter for Cancer Systems Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, USA. gimelbrant+lab@gmail.com.ORCID http://orcid.org/0000-0001-6986-0285

Funding

Mechanism and function of autosomal analog of X inactivationR01GM114864 · NIGMS · DANA-FARBER CANCER INST · PI GIMELBRANT, ALEXANDER · 2014 to 2018
$4.9M
Assessing parent-of-origin transcriptional effects in Xenopus laevisR21HD081675 · NICHD · DANA-FARBER CANCER INST · PI GIMELBRANT, ALEXANDER · 2014 to 2015
$465k
NICHD NIH HHS R21 HD081675NIGMS NIH HHS R01 GM114864
6 · The paper itself

Abstract

A sensitive approach to quantitative analysis of transcriptional regulation in diploid organisms is analysis of allelic imbalance (AI) in RNA sequencing (RNA-seq) data. A near-universal practice in such studies is to prepare and sequence only one library per RNA sample. We present theoretical and experimental evidence that data from a single RNA-seq library is insufficient for reliable quantification of the contribution of technical noise to the observed AI signal; consequently, reliance on one-replicate experimental design can lead to unaccounted-for variation in error rates in allele-specific analysis. We develop a computational approach, Qllelic, that accurately accounts for technical noise by making use of replicate RNA-seq libraries. Testing on new and existing datasets shows that application of Qllelic greatly decreases false positive rate in allele-specific analysis while conserving appropriate signal, and thus greatly improves reproducibility of AI estimates. We explore sources of technical overdispersion in observed AI signal and conclude by discussing design of RNA-seq studies addressing two biologically important questions: quantification of transcriptome-wide AI in one sample, and differential analysis of allele-specific expression between samples.

Indexed as

Allelic ImbalanceGene LibraryPolymorphism, Single NucleotideAlgorithmsAllelesAnimalsFemaleMiceMice, 129 StrainModels, GeneticRNASequence Analysis, RNATranscriptomeRNA

Identifiers

PMID34099647
PMCPMC8184992

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.