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ABDS: tool suite for analyzing biologically diverse samples.

Dongping Du1, Saurabh Bhardwaj1,2, Sarah J Parker3

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

Biorxiv : the Preprint Server for Biology
|July 18, 2023
PubMed
Summary
This summary is machine-generated.

The ABDS tool suite enhances the analysis of biologically diverse samples by improving missing value imputation, signature gene detection, and expression pattern visualization for more accurate molecular signal detection.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Standard analytics tools struggle with biologically diverse samples due to complex missing data patterns and multi-group comparisons.
  • Accurate identification of molecular features is crucial for understanding phenotypic variations.

Approach:

  • Developed the ABDS (Analysis of Biologically Diverse Samples) tool suite in open-source R scripts.
  • Implemented mechanism-integrated group-wise imputation to handle informative missingness in signature genes.
  • Extended cosine-based one-sample test for robust signature gene detection and designed a unified heatmap for comparative visualization.

Key Points:

  • ABDS specifically addresses challenges in analyzing heterogeneous biological data.
  • The suite offers improved methods for imputation, gene detection, and visualization.
  • Tools are designed to complement existing bioinformatics workflows.

Conclusions:

  • ABDS enables more accurate detection of interpretable molecular signals in diverse phenotypic samples.
  • The tool suite facilitates a deeper understanding of complex biological systems.
  • Freely available R scripts promote accessibility and adoption in biological research.