Dr.Tom is a web-based solution for the convenient analysis, visualisation and interpretation of all types of RNA data, including small RNAseq, miRNA and lncRNA.
Designed by a team of expert RNA scientists and bioinformaticians at BGI with collective experience across thousands of RNA based research projects, Dr.Tom provides a wide range of intuitive and interactive data visualisation tools specifically designed to save you time in your differential expression or pathway analysis research.
In addition, powerful analysis tools and advanced algorithms allow you to mine your data to gain new insight and more value beyond standard available RNA analysis services.
Data from many of the world’s leading databases have been integrated into the Dr.Tom system allowing users to reference and cross check all results and findings.
Dr.Tom is already relied upon by hundreds of scientists and researchers, and has shown itself to be a valuable and important tool in addition to any institution’s own internal data curation and analysis efforts. To learn more, email us for a no obligation discussion about access.
Dr.Tom’s detailed, interactive heatmap functionality can be used to quickly identify genes that are commonly regulated. With simple point-and-click action, data can be selected and manipulated to show clusters under different pathways.
Gene Set Enrichment Analysis
Dr.Tom accesses both free and licensed KEGG databases to allow users to conveniently and quickly find statistically significant trends in the large lists of genes generated by many functional genomics techniques and bioinformatics analyses approaches.
With a simple click Dr.Tom lets users detect RNA association with target genes, based on their interaction relationship (such as PPI, Target, Co-expression, ceRNA, GGI and RNAplex), or based on the position relationship (such as upstream and downstream position).
Reference Ontological Information Across Multiple Databases
Dr.Tom is able to reference multiple-databases for association analysis，including TCGA, NCBI and many more. This allows a user to quickly and conveniently view comprehensive ontological information for any gene of interest, including annotation, sequences, expression level, and a list of relevant published papers.
Customers can upload their own gene expression data, using tool boxes for graphing and visualisation, and construct their own gene annotation database for enrichment, clustering and multi-omics association analysis.
The researchers wanted to study the mechanism of poor prognosis of chidamide and MI-3 (hereinafter referred to as C and M) inhibitors for synergistic treatment of mixed leukemia (MLL) gene recombination. They utilised multiple Dr.Tom analysis functions to help answer several questions key to their paper. Some of these questions and how they were answered are listed below.
1. The researchers wanted to know what are the pathways for change after processing?
KEGG enrichment analysis showed that when C and M were combined, the most significant pathways were cell cycle, DNA replication, and repair pathways.