GenTIGS: A database empowering research and clinical insights on rare genetic disorders with an Indian perspective
Rashid, I.; S, P.; Moharir, S.; Mishra, R.
Show abstract
Rare Genetic Diseases (RGDs) are conditions caused by gene mutations affecting less than 1 in 2,000 individuals, as per World Health Organization (WHO). India, being the most populous country in the world has a high prevalence of these diseases. The situation is worsened further due to the practice of consanguinity in several communities and limited genetic testing. Multiple recent developments, including advancements in genetic sequencing, precision medicine and patient advocacy supported by collaborative networks and government initiatives offer hope for improved diagnosis and treatment. With an objective to bring what is known about these rare disorders on a single platform for the researchers, clinicians and various stakeholders, we have developed a database, GenTIGS, that is a to go platform for information about these diseases. GenTIGS is a comprehensive database, that includes the information about the genes and pathogenic variants, clinical symptoms for in-depth exploration of RGDs with a focus on globally reported disorders, especially those prevalent in India. For facilitating ease of use, GenTIGS encompasses an array of features and data points crucial for researchers and clinicians delving into RGD domains, ensuring efficient information retrieval. This data delivery system provides information on 2315 RGDs and 2779 associated genes, including 707 globally reported disorders prevalent in India. It also includes details on 3525 clinical symptoms and 307340 pathogenic variants for these disorders. GenTIGS provides extensive data, comprehensive range of analytical tools and resources for researchers, clinicians, and academicians, facilitating in-depth exploration of genes and variants associated with rare genetic disorders and features supporting advancements in genetic medicine by enhancing understanding and analysis within the scientific and clinical community. Accessible: https://db.tigs.res.in/gentigs/
Matching journals
The top 12 journals account for 50% of the predicted probability mass.