deepTools – simply analyse the genome

The open-source software deepTools provides efficient and easy-to-handle tools for advanced deep sequencing analyses.

Over the last 10 years, genome sequencing has become cheaper, faster and more precise. Thus, the amount of generated data increases rapidly. Due to the enormous size and complexity, data analysis typically takes a long time. Now, scientists at the Max Planck Institute of Immunobiology and Epigenetics have developed a software that – in a fraction of the time – standardizes and transparently processes DNA sequencing data, leading to facilitated comparability of experiments. The open-source software is readily accessible for everyone through a web platform. The software and its documentation were published in the well-known Journal Nucleic Acids Research.

With the completion of the Human Genome Project in 2000, DNA sequencing found its way into the scientific daily life. Improved methods and optimized computation processes reduced the time from sample generation to data analysis by a factor of 1000. “Today, the bottleneck is not reading out of the DNA code, but the data interpretation. Here, our software deepTools makes an important contribution,” said Dr. Thomas Manke, head of the Bionformatics group at the MPI of Immunobiology and Epigenetics. The open-source software deepTools as well as a comprehensive documentation are online available as freeware (http://deeptools.github.io).

deepTools executes all relevant analytic steps that are necessary for (deep) sequencing analysis: after the high throughput sequencing of the DNA, deepTools can perform quality controls and statistical normalizations. Importantly, the software is also available through an open web platform called ‘Galaxy’, which was developed in collaboration with computer scientists at the University of Freiburg. This is intended to facilitate the access to the software for non-computer scientists. “Thanks to the ease of use with Galaxy and the detailed instructions with lots of practical examples, scientists can analyze their own data with deepTools. This makes them more flexible and independent than before,” explains Friederike Dündar, co-first author of the publication.

 Due to customized workflows and optimized utilization of computer capacities, deepTools performs analyses in a fraction of the time that was previously required. Decoupling data analysis from data visualization makes the analyses even more efficient.

Unlike most previous software solutions, deepTools was designed to serve a great variety of applications and needs. Stringent standardization and detailed documentation of the software package significantly facilitates comparability between different experiments and research groups. “One of our main goals was to improve this comparability. Scientists can thus save time in data preparation and formatting, and rather use it for data interpretation,” says Dr. Fidel Ramirez, co-first author of the publication.