A web-oriented software for the optimization of pooled experiments in NGS for detection of rare mutations

BMC Res Notes. 2016 Feb 17:9:111. doi: 10.1186/s13104-016-1889-6.

Abstract

Background: The cost per patient of next generation sequencing for detection of rare mutations may be significantly reduced using pooled experiments. Recently, some techniques have been proposed for the planning of pooled experiments and for the optimal allocation of patients into pools. However, the lack of a user friendly resource for planning the design of pooled experiments forces the scientists to do frequent, complex and long computations.

Results: OPENDoRM is a powerful collection of novel mathematical algorithms usable via an intuitive graphical user interface. It enables researchers to speed up the planning of their routine experiments, as well as, to support scientists without specific bioinformatics expertises. Users can automatically carry out analysis in terms of costs associated with the optimal allocation of patients in pools. They are also able to choose between three distinct pooling mathematical methods, each of which also suggests the optimal configuration for the submitted experiment. Importantly, in order to keep track of the performed experiments, users can save and export the results of their experiments in standard tabular and charts contents.

Conclusion: OPENDoRM is a freely available web-oriented application for the planning of pooled NGS experiments, available at: http://www-labgtp.na.icar.cnr.it/OPENDoRM. Its easy and intuitive graphical user interface enables researchers to plan theirs experiments using novel algorithms, and to interactively visualize the results.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Computational Biology / methods
  • Computational Biology / statistics & numerical data*
  • DNA / analysis*
  • DNA / genetics
  • High-Throughput Nucleotide Sequencing / methods
  • High-Throughput Nucleotide Sequencing / statistics & numerical data*
  • Humans
  • Internet
  • Mutation*
  • User-Computer Interface*

Substances

  • DNA