Evidence map›Paper›PMID 39682398›Full record

ArticleAnimals : an open access journal from MDPI2024

Contamination Survey of Insect Genomic and Transcriptomic Data.

Jiali Zhou, Xinrui Zhang, Yujie Wang, Haoxian Liang, Yuhao Yang, Xiaolei Huang, Jun Deng

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Jiali ZhouState Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Xinrui ZhangState Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Yujie WangState Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Haoxian LiangState Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Yuhao YangState Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Xiaolei HuangState Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, China.ORCID 0000-0002-6839-9922
Jun DengState Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, China.

Funding

the Special Investigation Program for National Science and Technology Basic Resources, the Special Fund for Science and Technology Innovation of Fujian Agriculture and Forestry University 2022FY100500, KFB23016
6 · The paper itself

Abstract

The rapid advancement of high-throughput sequencing has led to a great increase in sequencing data, resulting in a significant accumulation of contamination, for example, sequences from non-target species may be present in the target species' sequencing data. Insecta, the most diverse group within Arthropoda, still lacks a comprehensive evaluation of contamination prevalence in public databases and an analysis of potential contamination causes. In this study, COI barcodes were used to investigate contamination from insects and mammals in GenBank's genomic and transcriptomic data across four insect orders. Among the 2796 WGS and 1382 TSA assemblies analyzed, contamination was detected in 32 (1.14%) WGS and 152 (11.0%) TSA assemblies. Key findings from this study include the following: (1) TSA data exhibited more severe contamination than WGS data; (2) contamination levels varied significantly among the four orders, with Hemiptera showing 9.22%, Coleoptera 3.48%, Hymenoptera 7.66%, and Diptera 1.89% contamination rates; (3) possible causes of contamination, such as food, parasitism, sample collection, and cross-contamination, were analyzed. Overall, this study proposes a workflow for checking the existence of contamination in WGS and TSA data and some suggestions to mitigate it.

Indexed as

COI barcodingcontaminationgenomic/transcriptomic databaseInsectasource

Identifiers

PMID39682398
PMCPMC11639764

What OpenQuestion holds

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Registered trials

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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.