Skip to main content
Explore URMC
URMC / Labs / Thakar Lab / Software



GESPA (GEnomic Single nucleotide Polymorphism Analyzer)

GESPA (GEnomic Single nucleotide Polymorphism Analyzer) is a bioinformatics tool for classifying Nonsynonymous Single Nucleotide Polymorphisms (nsSNPs). GESPA predicts if a nsSNP is pathogenic using reports from literature and various algorithms to assess conservation in orthologous and paralogous protein alignments. Using reports from literature, GESPA is also able to predict the phenotype of a nsSNP with high accuracy. The software can be used clinically to determine if observed nsSNPs are associated with disease. A host of annotations are provided: orthologous and paralogous multiple sequence alignments, UCSC annotations, reports detailing conservation of a nsSNP in alignments, and links to external nsSNP and gene information such as relevant publications. GESPA is connected to a constantly updating SQL server allowing for fast data retrieval. NOTE: REQUIRES Java 1.7.0+. Port 1433 cannot be blocked by firewall, network, or antivirus program.


  • Classifies nsSNPs by pathogenicity with sensitivity of 96.3%, specificity of 79.3%, and balanced accuracy of 87.8%
  • Can be used clinically to determine risk for diseases caused by nsSNPs
  • Predicts nsSNP phenotype correctly 96% of time when data is available
  • Provides useful annotations including UCSC Genome Browser annotations, homologous nucleotide and protein multiple sequence alignments, external nsSNP and gene information (ex. publications)
  • Connected to constantly updating SQL Server which allows for fast data retrieval and up to date information
  • Allows for versatile nsSNP input: amino acid location with change, dbSNP accession number, nucleotide location with change, nucleotide flanking sequence with change
  • Settings allow for control of phenotype prediction, pathogenicity prediction, paralogous genes, and SQL server data retrieval
  • Supports batch files


Download from SourceForge

BETA: Bayesian Estimation of Transcription Factor Activity

Reference: Comparative analysis of anti-viral transcriptomics reveals novel effects of influenza immune antagonism. Thakar J, Hartmann BM, Marjanovic N, Sealfon SC, Kleinstein SH. BMC Immunol. 2015 Aug 14;16(1):46. doi: 10.1186/s12865-015-0107-y.


Download BETA: Bayesian Estimation of Transcription Factor Activity from Yale