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InSNP: A tool for automated detection and visualization of SNPs and InDels
Author(s) -
Manaster Carl,
Zheng Weiyue,
Teuber Markus,
Wächter Stefan,
Döring Frank,
Schreiber Stefan,
Hampe Jochen
Publication year - 2005
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.20188
Subject(s) - indel , international hapmap project , biology , single nucleotide polymorphism , genetics , mutation , computational biology , human genome , indel mutation , snp , software , data mining , computer science , bioinformatics , gene , genome , genotype , programming language
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/ . Hum Mutat 26(1), 11–19, 2005. © 2005 Wiley‐Liss, Inc.