Evidence map›Paper›PMID 36100435›Full record

ArticleGenome research2022

Surveying mutation density patterns around specific genomic features.

Hui Yu, Scott Ness, Chung-I Li, Yongsheng Bai, Peng Mao, Yan Guo

Abstract read
In one paragraph

Article in Genome research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Comprehensive Pan-Cancer Mutation Density Patterns in Enhancer RNA.International journal of molecular sciences · 2023
    Article
  5. Strand asymmetries across genomic processes.Computational and structural biotechnology journal · 2023
    Review
  6. 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.

Hui YuComprehensive Cancer Center, Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico 87109, USA.
Scott NessComprehensive Cancer Center, Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico 87109, USA.
Chung-I LiDepartment of Statistics, National Cheng Kung University, Tainan, Taiwan 701401.
Yongsheng BaiComprehensive Cancer Center, Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico 87109, USA.
Peng MaoComprehensive Cancer Center, Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico 87109, USA.
Yan GuoComprehensive Cancer Center, Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico 87109, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mutation density patterns reveal unique biological properties of specific genomic regions and shed light on the mechanisms of carcinogenesis. Although previous studies reported insightful mutation density patterns associated with certain genomic regions such as transcription start sites and DNA replication origins, a tool that can systematically investigate mutational spatial patterns is still lacking. Thus, we developed MutDens, a bioinformatic tool for comprehensive analysis of mutation density patterns around genomic features, namely, genomic positions, in humans and model species. By scanning the bidirectional vicinity regions of given positions, MutDens systematically characterizes the mutation density for single-base substitution mutational classes after adjusting for total mutation burden and local nucleotide proportion. Analysis results using MutDens not only verified the previously reported transcriptional strand bias around transcription start sites and replicative strand bias around DNA replication origins, but also identified novel mutation density patterns around other genomics features, such as enhancers and retrotransposon insertion polymorphism sites. To our knowledge, MutDens is the first tool that systematically calculates, examines, and compares mutation density patterns, thus providing a valuable avenue for investigating the mutational landscapes associated with important genomic features.

Indexed as

GenomicsReplication OriginDNAHumansMutationTranscription Initiation SiteDNA

Identifiers

PMID36100435
PMCPMC9712630

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.