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Integrated approaches for genomic variation discovery using high throughput sequencing

Final Report Summary - IAGVDHTS (Integrated approaches for genomic variation discovery using high throughput sequencing)

IAGVDHTS aimed to develop and improve methods to discover genomic variation using the high throughput sequencing (HTS) platforms. For this purpose, we proposed new algorithms and improve existing ones to enable the discovery of previously uncharacterized forms of genomic structural variation. Another aim of the IAGVDHTS project was to take advantage of different strengths of different sequencing platforms and different library construction methods.

This project aimed to fill in the efficient analysis gap: through integrating detection approaches and building a single, “one stop” genome analysis package, we will reduce the computational workload for variant discovery. The proposed research is transformative of several fields of research because it will enable fast analysis of HTS data by minimizing computational overhead of using many different tools and read mappers for different classes of variation, which will hopefully lead to faster discoveries in science and medicine.

During this project we worked on 1) algorithms to improve speed, accuracy, and sensitivity of read mapping tools, 2) algorithms to map reads from newer sequencing platforms, 3) tools to characterize copy number variation using data from different sequencing platforms, 4) algorithms to discover large genomic inversions using pooled clone sequencing data, and 5) a new tool to incorporate different sequence signatures for structural variation into a single package.

The project resulted in one direct journal publication, one indirect journal publication, and one more indirect journal publication that is currently under review. We are also preparing one more direct journal publication to be submitted by the end of May 2016 to the Genome Biology journal, and the current preprint of this manuscript is already available on the preprint server bioRxiv. During the project, one M.Sc. student was supported, who graduated in August 2015, and continued as a PhD student. A new Ph.D. student joined the project at a late stage (March 2016), and he continues to work on problems in line with this project. We also supported one internship student from India and one from Iran was also supported for three months each in Summer 2014.

The project website is available at