Evidence map›Paper›PMID 29507534›Full record

ArticleBiological procedures online2018

Silhouette Scores for Arbitrary Defined Groups in Gene Expression Data and Insights into Differential Expression Results.

Shitao Zhao, Jianqiang Sun, Kentaro Shimizu, Koji Kadota

Abstract read
In one paragraph

Article in Biological procedures online, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

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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

22 citing papers in PubMed.

  1. Article
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  4. Progress in Assessing Retinal Microglia Using Single-Cell RNA Sequencing.Advances in experimental medicine and biology · 2025
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  9. Machine Learning of Functional Connectivity to Biotype Alcohol and Nicotine Use Disorders.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2024
    Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

4 authors.

Shitao ZhaoGraduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657 Japan.
Jianqiang SunGraduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657 Japan.
Kentaro ShimizuGraduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657 Japan.
Koji KadotaGraduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657 Japan.ORCID 0000-0002-3907-4336

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHierarchical Sample clustering (HSC) is widely performed to examine associations within expression data obtained from microarrays and RNA sequencing (RNA-seq). Researchers have investigated the HSC results with several possible criteria for grouping (e.g., sex, age, and disease types). However, the evaluation of arbitrary defined groups still counts in subjective visual inspection.

resultsTo objectively evaluate the degree of separation between groups of interest in the HSC dendrogram, we propose to use

conclusionSilhouettes is useful for exploring data with predefined group labels. It would help provide both an objective evaluation of HSC dendrograms and insights into the DE results with regard to the compared groups.

Indexed as

BioinformaticsDifferential expression analysisHierarchical sample clusteringSilhouettes

Identifiers

PMID29507534
PMCPMC5831220

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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.