%0 Journal Article %1 Manaster2005 %A Manaster, C %A Zheng, WY %A Teuber, M %A Wachter, S %A Doring, F %A Schreiber, S %A Hampe, J %C DIV JOHN WILEY & SONS INC, 111 RIVER ST, HOBOKEN, NJ 07030 USA %D 2005 %I WILEY-LISS %J Human Mutation %K SNP automation detection mutation software %N 1 %P 11--19 %T InSNP: A tool for automated detection and visualization of SNPs and InDels %V 26 %X 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. (c) 2005 Wiley-Liss, Inc.

@article{Manaster2005, 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. (c) 2005 Wiley-Liss, Inc.}}, added-at = {2011-01-17T13:09:51.000+0100}, address = {{DIV JOHN WILEY \& SONS INC, 111 RIVER ST, HOBOKEN, NJ 07030 USA}}, affiliation = {Hampe, J (Reprint Author), Univ Kiel, Natl Genotyping Platform, Inst Clin Mol Biol, Schittenhelmstr 12, D-24105 Kiel, Germany. Univ Kiel, German Natl Genotyping Platform, Kiel Ctr, Univ Klinikum Schleswig Holstein, Kiel, Germany. Univ Kiel, Inst Clin Mol Biol, Univ Klinikum Schleswig Holstein, Kiel, Germany. Fed Inst Food Safety, Kiel, Germany.}, author = {Manaster, C and Zheng, WY and Teuber, M and Wachter, S and Doring, F and Schreiber, S and Hampe, J}, biburl = {https://www.bibsonomy.org/bibtex/22fca5607b6403ef783c68dd7ee14d34d/hkayabilisim}, category = {Genetics \& Heredity}, cited = {13}, email = {J.Hampe@mucosa.de}, file = {:home/hkaya/Projeler/diagnus/Screener/doc/literature/Manaster2005.pdf:PDF}, id = {ISI:000230277400002}, interhash = {4ad1f8bf8eac37e719d0542ce085b647}, intrahash = {2fca5607b6403ef783c68dd7ee14d34d}, iso = {Hum. Mutat.}, issn = {1059-7794}, journal = {{Human Mutation}}, keywords = {SNP automation detection mutation software}, language = {English}, month = {{Jul}}, number = {{1}}, pages = {{11--19}}, publisher = {{WILEY-LISS}}, references = {10}, review = {Mutation Screener Putative = candidate mutations Actual SNP's Drawbacks: -Needs primer sequences -Does not work with low number of traces -Introduction Variations Importance of variations in haplotype research Haplotype analysis require large number of traces Previously used software for this purpose Why develop a new one Features of our software -Materials and Methods -Workflow Basic flow of the software SNP detection steps in short InDel detection strategy in short -Visualizations and Algorithms A very short description of InSNP -Sequence Alignment Simple word matching strategy -Basecalling Mostly relies on ABI/SCF calles Also makes its own calls for mutation frequency Allele detection based on basic peak area threshold -SNP detection Differences from reference are candidates}, timestamp = {2011-01-17T13:21:20.000+0100}, title = {{InSNP: A tool for automated detection and visualization of SNPs and InDels}}, type = {{Article}}, volume = {{26}}, year = {{2005}} }