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

Dongping Du¹, Saurabh Bhardwaj^1,2, Yingzhou Lu¹

¹Department of Electrical & Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.

Research Square

|June 10, 2024

Summary

The ABDS tool suite enhances bioinformatics analysis for diverse biological samples. It improves missing value imputation, signature gene detection, and visualization for more accurate molecular signal identification.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Bioinformatics software is crucial for identifying molecular features distinguishing phenotypic groups.
Common tools struggle with biologically diverse samples, high missing data rates, and complex comparisons.
Accurate analysis requires robust methods for missing value imputation, signature gene detection, and visualization.

Purpose of the Study:

To develop a bioinformatics tool suite (ABDS) for analyzing biologically diverse samples.
To address limitations in handling informative missingness and parallel group comparisons.
To enable more accurate detection of interpretable molecular signals.

Main Methods:

Developed a mechanism-integrated group-wise pre-imputation scheme to preserve informative missingness.
Extended a cosine-based one-sample test for detecting group-silenced signature genes.
Designed a unified heatmap for displaying multiple sample groups simultaneously.

Main Results:

The ABDS tool suite effectively analyzes biologically diverse samples.
Demonstrated effectiveness through comparative evaluations and biomedical showcases.
The proposed methods retain informative missingness and accurately detect signature genes.

Conclusions:

ABDS is an open-source R package complementing existing bioinformatics tools.
Enables biologists to more accurately detect molecular signals in diverse sample groups.
Improves the analysis of complex biological data with missing values and multiple groups.