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Related Experiment Video

Updated: Jun 25, 2025

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

Published on: October 27, 2017

danRerLib: a Python package for zebrafish transcriptomics.

Ashley V Schwartz¹, Karilyn E Sant^1,2, Uduak Z George^1,3

¹Computational Science Research Center, College of Sciences, San Diego State University, San Diego, CA 92182, United States.

Bioinformatics Advances

|May 21, 2024

Summary

This summary is machine-generated.

This study introduces danRerLib, a Python package for zebrafish transcriptomics. It enhances functional enrichment analysis by using human gene orthologs, improving insights into differential gene expression in zebrafish models.

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Last Updated: Jun 25, 2025

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

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Published on: October 27, 2017

Profiling DNA Replication Timing Using Zebrafish as an In Vivo Model System

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RNA Isolation from Embryonic Zebrafish and cDNA Synthesis for Gene Expression Analysis

RNA Isolation from Embryonic Zebrafish and cDNA Synthesis for Gene Expression Analysis

Published on: August 7, 2009

Area of Science:

Transcriptomics
Bioinformatics
Zebrafish model organism research

Background:

Differential gene expression analysis is crucial for understanding biological responses.
Zebrafish transcriptomes closely resemble humans, making them valuable disease models.
Incomplete zebrafish pathway annotations can bias functional enrichment results.

Purpose of the Study:

To address the challenge of incomplete zebrafish pathway annotations in functional enrichment analysis.
To introduce danRerLib, a Python package designed to improve zebrafish transcriptomics research.
To enable more comprehensive functional enrichment analysis by leveraging human orthologs.

Main Methods:

Developed danRerLib, a Python package for zebrafish transcriptomics.
Implemented tools for gene ID mapping and orthology mapping between zebrafish and human.
Integrated updated Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases for functional enrichment.

Main Results:

danRerLib facilitates functional enrichment analysis for GO and KEGG pathways.
The package enables analysis even for pathways lacking direct zebrafish annotations via human orthology.
This approach extends the scope of pathway analysis, providing deeper biological insights.

Conclusions:

danRerLib overcomes limitations of incomplete zebrafish annotations for functional enrichment.
The package enhances the ability to interpret differential gene expression in zebrafish models.
Researchers can gain greater insight into experimental results by utilizing danRerLib.