BACKGROUND: A wide variety of short-read alignment programmes have been 
published recently to tackle the problem of mapping millions of short reads to a 
reference genome, focusing on different aspects of the procedure such as time 
and memory efficiency, sensitivity, and accuracy. These tools allow for a small 
number of mismatches in the alignment; however, their ability to allow for gaps 
varies greatly, with many performing poorly or not allowing them at all. The 
seed-and-extend strategy is applied in most short-read alignment programmes. 
After aligning a substring of the reference sequence against the high-quality 
prefix of a short read--the seed--an important problem is to find the best 
possible alignment between a substring of the reference sequence succeeding and 
the remaining suffix of low quality of the read--extend. The fact that the reads 
are rather short and that the gap occurrence frequency observed in various 
studies is rather low suggest that aligning (parts of) those reads with a single 
gap is in fact desirable.
RESULTS: In this article, we present libgapmis, a library for extending pairwise 
short-read alignments. Apart from the standard CPU version, it includes 
ultrafast SSE- and GPU-based implementations. libgapmis is based on an algorithm 
computing a modified version of the traditional dynamic-programming matrix for 
sequence alignment. Extensive experimental results demonstrate that the 
functions of the CPU version provided in this library accelerate the 
computations by a factor of 20 compared to other programmes. The analogous SSE- 
and GPU-based implementations accelerate the computations by a factor of 6 and 
11, respectively, compared to the CPU version. The library also provides the 
user the flexibility to split the read into fragments, based on the observed gap 
occurrence frequency and the length of the read, thereby allowing for a 
variable, but bounded, number of gaps in the alignment.
CONCLUSIONS: We present libgapmis, a library for extending pairwise short-read 
alignments. We show that libgapmis is better-suited and more efficient than 
existing algorithms for this task. The importance of our contribution is 
underlined by the fact that the provided functions may be seamlessly integrated 
into any short-read alignment pipeline. The open-source code of libgapmis is 
available at http://www.exelixis-lab.org/gapmis.