Biostatistics in Genetic Research

DNA Analysis software processes huge amount of data. Genetic analysis needs software which can quickly collect, aggregate, interpret and visualize information. Axmor company has been developing custom DNA barcoding software and applications for more than 7 years. Learn more about our expertise and services.


A US Cancer Institute conducts research on individual genetic predisposition to cancer. Scientists in one of its laboratories suggested using DNA barcoding in their experiments. Statistical methods used for DNA barcode analysis require intensive computations, so the laboratory needed custom bioinformatics software for this task.

Software Solution

The Axmor engineers developed the software that analyzes DNA barcodes provided by researchers and compiles DNA barcode frequency matrices. Judging from these matrices, scientists can draw a conclusion regarding one’s genetic predisposition to cancer.

  • DNA barcode frequency matrix viewing, filtering, sorting, and searching
  • Data permutation
  • Data resampling
  • Ideal DNA barcode models generation

Higher Quality of Experiments

To obtain more accurate results, the software compares DNA barcodes with ideal models generated before the experiment and corrects errors in the barcodes to be analyzed.

Statistical Analysis of DNA barcodes

When elaborating the logic of DNA barcode analysis, we took advantage of various statistical methods used in computational biology for advanced data analysis and prediction. In particular, our developers extensively applied Markov chain Monte-Carlo methods, resampling, false discovery rate, and other techniques.


The software can simultaneously analyze DNA barcodes from a number of experiments. For a convenient display of the results, statistics located in one frequency matrix are automatically divided among respective parallel experiments.

High-performance Solution

  • The highest possible speed of DNA barcode processing by choosing a search-tree data structure.
  • The increase in the highest possible speed of data processing by 16 times using parallel calculations.
  • The speedup of memory allocation and de-allocation applying the “paged” memory management scheme.
  • The reduction in memory consumption by 25% for x64 by implementing certain computational optimization techniques.

Scientists widely use our software in their genetic research. The customer acknowledged our lead developer as a co-author of the elaborated approach in a research paper on the topic. We are proud that our customer highly appreciated the role Axmor played in the advancement of DNA barcoding. Now our team is ready to take on new and more challenging tasks in developing scientific software.


Core Technologies
C++, Objective-C

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