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Genome-wide prediction of splice-modifying SNPs in human genes using a new analysis pipeline called AASsites
BACKGROUND: Some single nucleotide polymorphisms (SNPs) are known to modify the risk of developing certain diseases or the reaction to drugs. Due to next generation sequencing methods the number of known human SNPs has grown. Not all SNPs lead to a modified protein, which may be the origin of a dise...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3194194/ https://www.ncbi.nlm.nih.gov/pubmed/21992029 http://dx.doi.org/10.1186/1471-2105-12-S4-S2 |
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author | Faber, Kirsten Glatting, Karl-Heinz Mueller, Phillip J Risch, Angela Hotz-Wagenblatt, Agnes |
author_facet | Faber, Kirsten Glatting, Karl-Heinz Mueller, Phillip J Risch, Angela Hotz-Wagenblatt, Agnes |
author_sort | Faber, Kirsten |
collection | PubMed |
description | BACKGROUND: Some single nucleotide polymorphisms (SNPs) are known to modify the risk of developing certain diseases or the reaction to drugs. Due to next generation sequencing methods the number of known human SNPs has grown. Not all SNPs lead to a modified protein, which may be the origin of a disease. Therefore, the recognition of functional SNPs is needed. Because most SNP annotation tools look for SNPs which lead to an amino acid exchange or a premature stop, we designed a new tool called AASsites which searches for SNPs which modify splicing. RESULTS: AASsites uses several gene prediction programs and open reading frame prediction to compare the wild type (wt) and the variant gene sequence. The results of the comparison are combined by a handmade rule system to classify a change in splicing as “likely, probable, unlikely”. Having received good results from tests with SNPs known for changing the splicing pattern we checked 80,000 SNPs from the human genome which are located near splice sites for their ability to change the splicing pattern of the gene and hereby result in a different protein. We identified 301 “likely” and 985 “probable” classified SNPs with such characteristics. Within this set 33 SNPs are described in the ssSNP Target database to cause modified splicing. CONCLUSIONS: With AASsites single SNPs can be checked for those causing splice modifications. Screening 80,000 known human SNPs we detected about 1,200 SNPs which probably modify splicing. AASsites is available at http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar using any web browser. |
format | Online Article Text |
id | pubmed-3194194 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-31941942011-10-17 Genome-wide prediction of splice-modifying SNPs in human genes using a new analysis pipeline called AASsites Faber, Kirsten Glatting, Karl-Heinz Mueller, Phillip J Risch, Angela Hotz-Wagenblatt, Agnes BMC Bioinformatics Research BACKGROUND: Some single nucleotide polymorphisms (SNPs) are known to modify the risk of developing certain diseases or the reaction to drugs. Due to next generation sequencing methods the number of known human SNPs has grown. Not all SNPs lead to a modified protein, which may be the origin of a disease. Therefore, the recognition of functional SNPs is needed. Because most SNP annotation tools look for SNPs which lead to an amino acid exchange or a premature stop, we designed a new tool called AASsites which searches for SNPs which modify splicing. RESULTS: AASsites uses several gene prediction programs and open reading frame prediction to compare the wild type (wt) and the variant gene sequence. The results of the comparison are combined by a handmade rule system to classify a change in splicing as “likely, probable, unlikely”. Having received good results from tests with SNPs known for changing the splicing pattern we checked 80,000 SNPs from the human genome which are located near splice sites for their ability to change the splicing pattern of the gene and hereby result in a different protein. We identified 301 “likely” and 985 “probable” classified SNPs with such characteristics. Within this set 33 SNPs are described in the ssSNP Target database to cause modified splicing. CONCLUSIONS: With AASsites single SNPs can be checked for those causing splice modifications. Screening 80,000 known human SNPs we detected about 1,200 SNPs which probably modify splicing. AASsites is available at http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar using any web browser. BioMed Central 2011-07-05 /pmc/articles/PMC3194194/ /pubmed/21992029 http://dx.doi.org/10.1186/1471-2105-12-S4-S2 Text en Copyright ©2011 Faber et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Faber, Kirsten Glatting, Karl-Heinz Mueller, Phillip J Risch, Angela Hotz-Wagenblatt, Agnes Genome-wide prediction of splice-modifying SNPs in human genes using a new analysis pipeline called AASsites |
title | Genome-wide prediction of splice-modifying SNPs in human genes using a new analysis pipeline called AASsites |
title_full | Genome-wide prediction of splice-modifying SNPs in human genes using a new analysis pipeline called AASsites |
title_fullStr | Genome-wide prediction of splice-modifying SNPs in human genes using a new analysis pipeline called AASsites |
title_full_unstemmed | Genome-wide prediction of splice-modifying SNPs in human genes using a new analysis pipeline called AASsites |
title_short | Genome-wide prediction of splice-modifying SNPs in human genes using a new analysis pipeline called AASsites |
title_sort | genome-wide prediction of splice-modifying snps in human genes using a new analysis pipeline called aassites |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3194194/ https://www.ncbi.nlm.nih.gov/pubmed/21992029 http://dx.doi.org/10.1186/1471-2105-12-S4-S2 |
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