Oasis: online analysis of small RNA deep sequencing data

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Small-RNA sequencing (sRNA-seq) is crucial for understanding gene regulation.
• Analyzing sRNA-seq data can be complex and time-consuming for lab-based researchers.
• Existing tools may lack comprehensive features for differential expression, biomarker discovery, and functional analysis.

Purpose of the Study:

• To introduce Oasis, a web application designed for efficient and flexible online analysis of sRNA-seq data.
• To provide an accessible platform for end-users in the lab with tutorials and guidelines.
• To offer advanced analytical capabilities including multivariate differential expression, biomarker detection, and functional enrichment.

Main Methods:

• Development of a web application with an intuitive user interface.
• Implementation of modules for differential expression analysis (multivariate), classification (biomarker detection), and functional enrichment (GO, pathway).
• Integration of an advanced programming interface for batch job submission and generation of interactive web reports.

Main Results:

• Oasis enables fast and flexible online analysis of sRNA-seq data.
• The application supports multivariate analysis of samples for differential expression.
• Biomarker detection and functional analyses, including novel miRNA and target identification, are integrated.
• Interactive web reports facilitate data visualization and exploration.

Conclusions:

• Oasis offers a powerful, user-friendly solution for sRNA-seq data analysis.
• Its modular design allows for rapid and repeatable data analysis.
• The platform empowers researchers with advanced bioinformatics tools for biological discovery.