Evidence map›Paper›PMID 30380071›Full record

ArticleNucleic acids research2019

DSMNC: a database of somatic mutations in normal cells.

Xuexia Miao, Xi Li, Lifei Wang, Caihong Zheng, Jun Cai

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.3field-weighted citation impact, top 46% of its field
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

13 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Pan-cancer analyses of synonymous mutations based on tissue-specific codon optimality.Computational and structural biotechnology journal · 2022
    Article
  12. Article
  13. 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

5 authors at 3 institutions in 1 country.

Xuexia MiaoKey Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Xi LiKey Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Lifei WangKey Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Caihong ZhengKey Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Jun CaiKey Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Beijing Institute of Genomics · CNUniversity of Chinese Academy of Sciences · CNChinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Numerous non-inherited somatic mutations, distinct from those of germ-line origin, occur in somatic cells during DNA replication per cell-division. The somatic mutations, recording the unique genetic cell-lineage 'history' of each proliferating normal cell, are important but remain to be investigated because of their ultra-low frequency hidden in the genetic background of heterogeneous cells. Luckily, the recent development of single-cell genomics biotechnologies enables the screening and collection of the somatic mutations, especial single nucleotide variations (SNVs), occurring in normal cells. Here, we established DSMNC: a database of somatic mutations in normal cells (http://dsmnc.big.ac.cn/), which provides most comprehensive catalogue of somatic SNVs in single cells from various normal tissues. In the current version, the database collected ∼0.8 million SNVs accumulated in ∼600 single normal cells (579 human cells and 39 mouse cells). The database interface supports the user-friendly capability of browsing and searching the SNVs and their annotation information. DSMNC, which serves as a timely and valuable collection of somatic mutations in individual normal cells, has made it possible to analyze the burdens and signatures of somatic mutations in various types of heterogeneous normal cells. Therefore, DSMNC will significantly improve our understanding of the characteristics of somatic mutations in normal cells.

Indexed as

Databases, Nucleic AcidMutationAnimalsDNA Mutational AnalysisHigh-Throughput Nucleotide SequencingHumansMiceSingle-Cell AnalysisUser-Computer Interface

Identifiers

PMID30380071
PMCPMC6323907
OpenAlexW2898761372

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.