In this paper we proposed an integrative strategy of gene prioritization which can employ various genetic resources, including gene expression data, SNP genotype data, and eQTL data, even if it is not limited to use these data only.
In this paper, we propose a meta-analysis strategy for gene prioritization which integrates three different genetic resources, namely, gene expression data, SNP genotype data, and eQTL data, with an improved technique for order of preference by similarity to ideal solution (TOPSIS) [ 17].
Expressed sequence tag (ESTs) databases, are the most abundant resource of gene expression data.
We present these data as a web-accessible resource containing gene expression data covering several aspects of legume development and symbiotic biology.
The microarray data obtained with Fusarium graminearum Affymetrix GeneChip were downloaded from Plant Expression Database (PLEXdb, http://www.plexdb.org/index.php), which is a unified public resource for gene expression data of plants and plant pathogens.
In this work, the microarray data obtained with F. graminearum Affymetrix GeneChip were downloaded from Plant Expression Database (PLEXdb, http://www.plexdb.org/index.php), which is a unified public resource for gene expression data of plants and plant pathogens.
Thus our results demonstrate the rich knowledge resource within gene expression data generated from human tissues.
BioGPS (an online resource containing gene expression data based on Affymetrix microarrays) was used to visualize and compare gene expression patterns for catenin family members and catenin-related genes in human and mouse cells [ 20].
The 24 raw hybridization intensity data files (.CEL files) for Arabidopsis seed development were retrieved from The Arabidopsis Information Resource (TAIR) gene expression data repository (http://www.arabidopsis.org/servlets/TairObject type=hyb_descr_collection&id=1006710873) [ 71].
The present study has demonstrated that RNA-Seq technology provides an efficient method for transcriptome analysis of non-model plant organisms, delivering a valuable resource of gene expression data for further analysis.
