Evidence map›Paper›PMID 37461566›Full record

ArticlebioRxiv : the preprint server for biology2023

ABDS: tool suite for analyzing biologically diverse samples.

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

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. 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

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.
Sarah J ParkerAdvanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA.
Zuolin ChengDepartment of Electrical & Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.
Zhen ZhangDepartment of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA.
Yingzhou LuDepartment of Electrical & Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.
Jennifer E Van EykAdvanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA.
Guoqiang YuDepartment of Electrical & Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.
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
Metabolomic Signatures of CAD Associated GenotypesR01HL133932 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI BOWDEN, DONALD W, HERRINGTON, DAVID MCLEOD · 2016 to 2019
$2.5M
NHLBI NIH HHS R01 HL111362NHLBI NIH HHS R01 HL133932NIMH NIH HHS R01 MH110504NINDS NIH HHS U19 NS123719
6 · The paper itself

Abstract

Motivation: Analytics tools are essential to identify informative molecular features about different phenotypic groups. Among the most fundamental tasks are missing value imputation, signature gene detection, and expression pattern visualization. However, most commonly used analytics tools may be problematic for characterizing biologically diverse samples when either signature genes possess uneven missing rates across different groups yet involving complex missing mechanisms, or multiple biological groups are simultaneously compared and visualized. Results: We develop ABDS tool suite tailored specifically to analyzing biologically diverse samples. Mechanism-integrated group-wise imputation is developed to recruit signature genes involving informative missingness, cosine-based one-sample test is extended to detect enumerated signature genes, and unified heatmap is designed to comparably display complex expression patterns. We discuss the methodological principles and demonstrate the conceptual advantages of the three software tools. We also showcase the biomedical applications of these individual tools. Implemented in open-source R scripts, ABDS tool suite complements rather than replaces the existing tools and will allow biologists to more accurately detect interpretable molecular signals among diverse phenotypic samples. Availability and implementation: The R Scripts of ABDS tool suite is freely available at https://github.com/niccolodpdu/ABDS.

Identifiers

PMID37461566
PMCPMC10349978

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.