GenomeGems - Evaluation of Genetic Variability from Deep Sequencing Data

GenomeGems’ aim is to provide investigators with a simple tool for sorting, analyzing, prioritizing and visualizing the Single Nucleotide Polymorphisms (SNPs) provided by bioinformatics analysis of data acquired by Deep Sequencing experiments. The key design feature is to facilitate the final steps of Deep Sequencing data analysis thus leading to a rapid shift to the next step of experimental mutation validation.

Deep Sequencing or "Next Generation Sequencing" is a revolutionary method that allows myriad amounts of short DNA fragments to be read simultaneously. Deep Sequencing of the human genome poses challenges for processing, analyzing, interpreting and then presenting the large volumes of data generated. The final stages of analysis are performed manually and are critical for mutation identification. GenomeGems, is a software package with the capability of organizing, analyzing (via tabular and graphical data comparisons) and visualizing specific features of Deep Sequencing data, essential for investigators studying disease-causing Small Nucleotide Polymorphisms (SNPs).

GenomeGems runs on a local PC, has a friendly interface and is integratable with UCSC Genome Browser and Microsoft Excel.

Run GenomeGems

  1. Make sure that you have all system requirements or install them.
  2. Download GenomeGems and start working.

More information

See our Manual Page for an overview of the GenomeGems workflow.

Download our Matlab Code to run GenomeGems application in Matlab 2009a.

Sample Datasets

  1. Sample Data of Novel SNPs:  SA1ExampleNovelSA2ExampleNovel
  2. Sample Data of Clinically-Associated SNPs: SA1ExampleCASA2ExampleCA


Questions, suggestions and bug reports are welcome at


GenomeGems and this site were generated  by Adi Givati 1,2*, Sharon Ben-Zvi 1,2* and Dr. Noam Shomron 2

1 Department of Biomedical Engineering, The Iby and Aladar Fleishman Faculty of Engineering, 2 Department of Cell and Developmental Biology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel. * Equal contribution.