Unit:
Κατεύθυνση Βιοπληροφορική-Υπολογιστική ΒιολογίαLibrary of the School of Science
Author:
Zogopoulos Vasileios
Supervisors info:
Βασιλική Οικονομίδου, Αναπληρώτρια Καθηγήτρια, Τμήμα Βιολογίας, Πανεπιστήμιο Αθηνών
Original Title:
HGCA και ACT: Εργαλεία για τη μελέτη της γονιδιακής συνέκφρασης στον άνθρωπο και το πρότυπο φυτό Arabidopsis thaliana
Translated title:
HGCA and ACT: Tools for the study of gene coexpression in human and model plant Arabidopsis thaliana
Summary:
Genes with similar expression patterns tend to participate in related biological processes. The most efficient way to study gene coexpression is based on the transcriptomic data analysis of the subset of samples which contain the best representatives of each tissue or cell type. The coexpression of genes revealed from a variety of transcriptomic experiments stored in public repositories, may contain information far beyond the original scope of each constituent experiment, and can be a valuable predictive tool for gene function and pathway membership. Three tools were developed: Arabidopsis Coexpression Tool (ACT) studies gene coexpression in model plant Arabidopsis thaliana, which is based on 3500 microarray samples from three different public repositories, Human Gene Coexpression Analysis (HGCA) 1.5 studies gene coexpression in human, which is based on 1959 microarray samples from GEO and HGCA2, again for human, based on 3500 RNA-seq samples from GTEx. Meticulous sample selection was performed in each case, novel data processing algorithms were used and genes were grouped using hierarchical clustering. The websites were developed using modern libraries. By typing a driver-gene, the tools output a coexpression subtree whose leaves contain genes coexpressed with the input gene. The user can perform a variety of biological term enrichment analyses upon the list of gene of the coexpression subtree. By studying the list of coexpressed genes and the enrichment analysis results, gene functional partners to the gene of interest can be discovered or a function can be assigned to a gene of unknown role by examining its coexpressed genes in neighbouring leaves.
Main subject category:
Science
Keywords:
Webtool, Microarrays, NGS, Gene Coexpression, Transcriptomics, Functional Annotation
Number of references:
125
