PEAR is an ultrafast, memory-efficient and highly accurate pair-end read merger. It is fully parallelized and can run with as low as just a few kilobytes of memory.
PEAR evaluates all possible paired-end read overlaps and without requiring the target fragment size as input. In addition, it implements a statistical test for minimizing false-positive results. Together with a highly optimized implementation, it can merge millions of paired end reads within a couple of minutes on a standard desktop computer.
An updated version of PEAR is released.
An updated version of PEAR is released.
An updated version of PEAR is released.
An updated version of PEAR is released.
An updated version of PEAR is released.
An updated version of PEAR is released.
An updated version of PEAR is released.
An updated version of PEAR is released.
An updated version of PEAR is released.
A basic version of the PEAR manual was added to the website.
The first version of PEAR is finally available. It is available as a standalone library and in source code format.
The PEAR creative commons license prohibits commercial use of the code. For testing and using PEAR on a commercial basis you need to purchase a commercial software license. If you wish to purchase such a license please contact: Prof. Alexandros Stamatakis
Morgan Langille at the Department of Pharmacology at Dalhousie University developed a wrapper perl script for PEAR that facilitates running it on many samples. It also captures the log output and reformats the output to a tab-delimited format (both logs are captured). The script is called run_pear.pl and it is available via Morgan's github repository.