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DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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Related Experiment Video

Updated: Aug 28, 2025

A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae

A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae

Published on: April 25, 2015

BioTEA: Containerized Methods of Analysis for Microarray-Based Transcriptomics Data.

Luca Visentin¹, Giorgia Scarpellino¹, Giorgia Chinigò¹

¹Department of Life Sciences and Systems Biology, University of Turin, 10123 Turin, Italy.

|September 23, 2022

Summary

This summary is machine-generated.

bioTEA is a new software tool for analyzing gene expression data from RNA-sequencing experiments. It simplifies complex transcriptomics analysis, ensuring reproducible results for researchers.

Keywords:

differential expression microarray reproducibility transcriptomics

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Vast amounts of gene expression data are publicly available in databases like GEO and ArrayExpress.
The shift from microarray to RNA-sequencing necessitates advanced analysis tools for data preservation and reproducibility.

Purpose of the Study:

To introduce bioTEA (biological Transcript Expression Analyzer), a novel software tool for comprehensive transcriptomics analysis.
To provide a user-friendly yet powerful platform for differential gene expression analysis from raw data to annotation.

Main Methods:

bioTEA is an R-coded pipeline with a Python command-line interface, containerized using Docker.
It offers customizable options for gene filtering, batch effect correction, sample pairing, and statistical test selection.
Analysis parameters are saved in a shareable text file for deterministic reproducibility.

Main Results:

bioTEA facilitates robust differential gene expression analysis from raw RNA-seq data.
The tool ensures reproducibility through detailed logging and shareable configuration files.
It integrates data retrieval, preparation, processing, and gene annotation.

Conclusions:

bioTEA is a versatile and powerful tool for transcriptomics research, suitable for bioinformaticians and wet-lab biologists.
The software promotes data accessibility and reproducible research in the field of gene expression analysis.
bioTEA is freely available as an open-source solution.