TransAtlasDB - an Informatics System for Transcriptome Analysis Data

High-throughput transcriptome sequencing (RNAseq) is the universally applied method for target-free transcript identification and gene expression quantification, generating huge amounts of data. The constraint of accessing such data and interpreting results can be a major impediment in postulating suitable hypothesis, thus the need for an organizational structure for easy storage of and access to results is important. By offering a uniform data storage and retrieval mechanism, various data can be compared and investigated easily. We present a sophisticated system, TransAtlasDB, which incorporates a hybrid architecture of both relational and NoSQL databases for fast and efficient data storage, processing and querying of large datasets from transcript expression analysis with corresponding metadata, as well as gene-associated variants (such as SNPs) and their predicted gene effects. TransAtlasDB also provides user-friendly data management workflows, written in Perl, with useful functionalities that simplifies the complexity of data storage and possibly manipulation of the massive amounts of data generated from RNAseq analysis. The main objective of TransAtlasDB is to serve as an accessible repository for large complex data derived from RNAseq gene expression profiling and variant analysis.