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.
For technical questions and support please use the PEAR google group at:
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 are a member of an academic institution and you use this software solely for research purposes, you can download this. Academic use is defined as the deployment of PEAR for the sole purpose of analyzing scientific data with the clear objective to (i) make all data and analyses publicly as well as freely available (ii) intend to publish the results of these data analyses in peer-reviewed scientific journals. Integration into and redistribution of PEAR in larger software pipelines requires prior written approval by the owners. All other uses of PEAR are considered as non-academic.
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