Evidence map›Paper›PMID 38853832›Full record

ArticleResearch square2024

ABDS: a bioinformatics tool suite for analyzing biologically diverse samples.

Dongping Du, Saurabh Bhardwaj, Yingzhou Lu, Yizhi Wang, Sarah J Parker, Zhen Zhang, Jennifer E Van Eyk, Guoqiang Yu, Robert Clarke, David M Herrington and 1 more

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PubMed Full text at PMC Publisher
In one paragraph

Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

5 · Who and what money

Authors and funding

11 authors.

Dongping DuDepartment of Electrical & Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.
Saurabh BhardwajDepartment of Electrical & Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.
Yingzhou LuDepartment of Electrical & Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.
Yizhi WangDepartment of Electrical & Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.
Sarah J ParkerAdvanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA.
Zhen ZhangDepartment of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA.
Jennifer E Van EykAdvanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA.
Guoqiang YuDepartment of Automation, Tsinghua University, Beijing 100084, P. R. China.
Robert ClarkeThe Hormel Institute, University of Minnesota, Austin, MN 55912, USA.
David M HerringtonDepartment of Internal Medicine, Wake Forest University, Winston-Salem, NC 27157, USA.
Yue WangDepartment of Electrical & Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.

Funding

Genomic and Proteomic Architecture of AtherosclerosisR01HL111362 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI HERRINGTON, DAVID MCLEOD · 2012 to 2021
$17.2M
Novel Genetically Encoded Indicators for Interrogating Neuron-Astrocyte Communication Across TimescalesU19NS123719 · NINDS · SALK INSTITUTE FOR BIOLOGICAL STUDIES · PI TIAN, LIN · 2021 to 2025
$10.7M
Decoding Astrocyte Signaling in Neural Circuitry with Novel Computational Modeling and Analytical ToolsR01MH110504 · NIMH · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI YUE WANG · 2017 to 2026
$6.1M
NHLBI NIH HHS R01 HL111362NIMH NIH HHS R01 MH110504NINDS NIH HHS U19 NS123719
6 · The paper itself

Abstract

Bioinformatics software tools are essential to identify informative molecular features that define different phenotypic sample groups. Among the most fundamental and interrelated tasks are missing value imputation, signature gene detection, and differential pattern visualization. However, many commonly used analytics tools can be problematic when handling biologically diverse samples if either informative missingness possess high missing rates with mixed missing mechanisms, or multiple sample groups are compared and visualized in parallel. We developed the ABDS tool suite specifically for analyzing biologically diverse samples. Collectively, a mechanism-integrated group-wise pre-imputation scheme is proposed to retain informative missingness associated with signature genes, a cosine-based one-sample test is extended to detect group-silenced signature genes, and a unified heatmap is designed to display multiple sample groups. We describe the methodological principles and demonstrate the effectiveness of three analytics tools under targeted scenarios, supported by comparative evaluations and biomedical showcases. As an open-source R package, ABDS tool suite complements rather than replaces existing tools and will allow biologists to more accurately detect interpretable molecular signals among phenotypically diverse sample groups.

Identifiers

PMID38853832
PMCPMC11160903

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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.