PAIR: polymorphic Alu insertion recognition.

ABSTRACT:

Background

Alu polymorphisms are some of the most common polymorphisms in the genome, yet few methods have been developed for their detection.

Methods

We present algorithms to discover Alu polymorphisms using paired-end high throughput sequencing data from multiple individuals. We consider the problem of identifying sites containing polymorphic Alu insertions.

Results

We give efficient and practical algorithms that detect polymorphic Alus, both those that are inserted with respect to the reference genome and those that are deleted. The algorithms have a linear time complexity and can be run on a standard desktop machine in a very short amount of time on top of the output of tools standard for sequencing analysis.

Conclusions

In our simulated dataset we are able

SUBMITTER: Sveinbjornsson JI 

PROVIDER: S-EPMC3358660 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature