Evidence map›Paper›PMID 38097965›Full record

ArticleBMC bioinformatics2023

Twnbiome: a public database of the healthy Taiwanese gut microbiome.

Amrita Chattopadhyay, Chien-Yueh Lee, Ya-Chin Lee, Chiang-Lin Liu, Hsin-Kuang Chen, Yung-Hua Li, Liang-Chuan Lai, Mong-Hsun Tsai, Yen-Hsuan Ni, Han-Mo Chiu and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 26% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. 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

12 authors at 3 institutions in 1 country.

Amrita ChattopadhyayBioinformatics and Biostatistics Core, Centers of Genomic and Precision Medicine, National Taiwan University, Taipei, Taiwan.
Chien-Yueh LeeDepartment of Biomedical Engineering, China Medical University, Taichung, Taiwan.
Ya-Chin LeeDepartment of Public Health, Institute of Health Data Analytics and Statistics, National Taiwan University, Taipei, Taiwan.
Chiang-Lin LiuGraduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.
Hsin-Kuang ChenCenter for Biotechnology, National Taiwan University, Taipei, Taiwan.
Yung-Hua LiGraduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.
Liang-Chuan LaiBioinformatics and Biostatistics Core, Centers of Genomic and Precision Medicine, National Taiwan University, Taipei, Taiwan.
Mong-Hsun TsaiBioinformatics and Biostatistics Core, Centers of Genomic and Precision Medicine, National Taiwan University, Taipei, Taiwan.
Yen-Hsuan NiCollege of Medicine, National Taiwan University, Taipei, Taiwan.
Han-Mo ChiuCollege of Medicine, National Taiwan University, Taipei, Taiwan.
Tzu-Pin LuBioinformatics and Biostatistics Core, Centers of Genomic and Precision Medicine, National Taiwan University, Taipei, Taiwan. tplu@ntu.edu.tw.
Eric Y ChuangBioinformatics and Biostatistics Core, Centers of Genomic and Precision Medicine, National Taiwan University, Taipei, Taiwan. chuangey@ntu.edu.tw.
National Taiwan University · TWNational Yang Ming Chiao Tung University · TWChina Medical University · TW

Funding

National Taiwan University GTZ-300
6 · The paper itself

Abstract

With new advances in next generation sequencing (NGS) technology at reduced costs, research on bacterial genomes in the environment has become affordable. Compared to traditional methods, NGS provides high-throughput sequencing reads and the ability to identify many species in the microbiome that were previously unknown. Numerous bioinformatics tools and algorithms have been developed to conduct such analyses. However, in order to obtain biologically meaningful results, the researcher must select the proper tools and combine them to construct an efficient pipeline. This complex procedure may include tens of tools, each of which require correct parameter settings. Furthermore, an NGS data analysis involves multiple series of command-line tools and requires extensive computational resources, which imposes a high barrier for biologists and clinicians to conduct NGS analysis and even interpret their own data. Therefore, we established a public gut microbiome database, which we call Twnbiome, created using healthy subjects from Taiwan, with the goal of enabling microbiota research for the Taiwanese population. Twnbiome provides users with a baseline gut microbiome panel from a healthy Taiwanese cohort, which can be utilized as a reference for conducting case-control studies for a variety of diseases. It is an interactive, informative, and user-friendly database. Twnbiome additionally offers an analysis pipeline, where users can upload their data and download analyzed results. Twnbiome offers an online database which non-bioinformatics users such as clinicians and doctors can not only utilize to access a control set of data, but also analyze raw data with a few easy clicks. All results are customizable with ready-made plots and easily downloadable tables. Database URL: http://twnbiome.cgm.ntu.edu.tw/ .

Indexed as

Gastrointestinal MicrobiomeMicrobiotaAlgorithmsComputational BiologyDatabases, FactualHigh-Throughput Nucleotide SequencingHumansSoftwareGut-microbiotaHealthy subjectsPublic databaseTaiwan population

Identifiers

PMID38097965
PMCPMC10722848
OpenAlexW4389731849

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.