InSNP: a tool for automated detection and visualization of SNPs and InDels.

Authors:
Carl Manaster, Weiyue Zheng, Markus Teuber, Stefan Wächter, Frank Döring, Stefan Schreiber, Jochen Hampe
Year of publication:
2005
Volume:
26
Issue:
1
Issn:
1059-7794
Journal title abbreviated:
HUM MUTAT
Journal title long:
Human mutation
Impact factor:
4.700
Abstract:
Availability of high quality SNP data is a rate-limiting factor in understanding the impact of genetic variability on gene function and phenotype. Although global projects like HAPMAP generate large numbers of SNPs in an even spacing throughout the human genome, many variation studies have a more focused approach: in the follow-up of positional association findings, candidate gene studies, and functional genomics experiments, knowledge of all variations in a limited amount of sequence (e.g., a gene) is needed. This leads to a large number of resequencing experiments, for which there is a surprising lack of analysis software. We have thus developed specialized software (InSNP) for targeted mutation detection and compared its performance to Polyphred and Mutation Surveyor using 28 amplicons. Out of a total of 579 (InSNP), 644 (Polyphred), and 526 (Mutation Surveyor) SNP predictions, 39 SNPs were confirmed by human expert inspection, with five SNPs missed by Polyphred and one missed by InSNP using the default settings. For InDel detection, out of 70 (InSNP), 28 (Polyphred), and 693 (Mutation Surveyor) InDel predictions, two InDels were confirmed by human expert inspection, with one InDel missed by Polyphred. InSNP provides a user-friendly interface with better functionality for mutation detection than general-purpose sequence handling software. It provides similar SNP detection sensitivity and specificity as the public domain and commercial alternatives in the investigated dataset. We hope that InSNP lowers the barriers to the use of automated mutation detection software and aids in the improvement of the efficiency of such experiments. The Windows installer (setup) program and sample datasets are available at www.mucosa.de/insnp/.