Evidence map›Paper›PMID 37745976›Full record

ArticleNAR genomics and bioinformatics2023

Underlying causes for prevalent false positives and false negatives in STARR-seq data.

Pengyu Ni, Siwen Wu, Zhengchang Su

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

3 authors.

Pengyu NiDepartment of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC 28223, USA.
Siwen WuDepartment of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC 28223, USA.
Zhengchang SuDepartment of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC 28223, USA.ORCID https://orcid.org/0000-0001-9878-5480

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Self-transcribing active regulatory region sequencing (STARR-seq) and its variants have been widely used to characterize enhancers. However, it has been reported that up to 87% of STARR-seq peaks are located in repressive chromatin and are not functional in the tested cells. While some of the STARR-seq peaks in repressive chromatin might be active in other cell/tissue types, some others might be false positives. Meanwhile, many active enhancers may not be identified by the current STARR-seq methods. Although methods have been proposed to mitigate systematic errors caused by the use of plasmid vectors, the artifacts due to the intrinsic limitations of current STARR-seq methods are still prevalent and the underlying causes are not fully understood. Based on predicted

Identifiers

PMID37745976
PMCPMC10516709

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.