Validation of deep sequencing data from Drosophila mauritiana: by classic Sanger sequencing
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Validation of deep sequencing data from Drosophila mauritiana by classic Sanger sequencing
DE PB NWISBN: 9783639491333 bzw. 3639491335, in Deutsch, AV Akademikerverlag, Taschenbuch, neu.
Von Händler/Antiquariat, BuySomeBooks [52360437], Las Vegas, NV, U.S.A.
Paperback. 56 pages. Dimensions: 8.7in. x 5.9in. x 0.1in.Massively parallel sequencing technology has a wide range of applications. Its use in SNP detection is already widespread and promises results of high accuracy. The aim is to validate data generated with the Genome Analyser II. SNPs, detected by using different mapping and SNP estimation parameters implemented in the bioinformatics tool CLC were compared to SNPs that are detected by using the method of conventional Sanger sequencing. Lines of D. mauritiana were used. As reference genome in CLC I was bound to use the genome of D. simulans, because there is no available genome of D. mauritiana until now. Using a stringent parameter set (short parameter set) that allows few mismatches of reads when mapping against the reference genome, only few regions are recovered which show divergence to the reference. 60-81 SNPs detected with this parameter set are false positive ones compared to Sanger sequencing. If a less stringent parameter set is used this results in a very high number of false positive SNPs. Two times more SNPs were recovered with this parameter set, thereof 70-80 are false positive ones. Based on my results I drew conclude that the best approach for SNP detection is to make one first run permitting a high number of mismatches. The next step should be the use of more stringent values to reduce the high number of false positive SNPs. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN.
Paperback. 56 pages. Dimensions: 8.7in. x 5.9in. x 0.1in.Massively parallel sequencing technology has a wide range of applications. Its use in SNP detection is already widespread and promises results of high accuracy. The aim is to validate data generated with the Genome Analyser II. SNPs, detected by using different mapping and SNP estimation parameters implemented in the bioinformatics tool CLC were compared to SNPs that are detected by using the method of conventional Sanger sequencing. Lines of D. mauritiana were used. As reference genome in CLC I was bound to use the genome of D. simulans, because there is no available genome of D. mauritiana until now. Using a stringent parameter set (short parameter set) that allows few mismatches of reads when mapping against the reference genome, only few regions are recovered which show divergence to the reference. 60-81 SNPs detected with this parameter set are false positive ones compared to Sanger sequencing. If a less stringent parameter set is used this results in a very high number of false positive SNPs. Two times more SNPs were recovered with this parameter set, thereof 70-80 are false positive ones. Based on my results I drew conclude that the best approach for SNP detection is to make one first run permitting a high number of mismatches. The next step should be the use of more stringent values to reduce the high number of false positive SNPs. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN.
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Validation of Deep Sequencing Data from Drosophila Mauritiana (Paperback) (2013)
DE PB NW RPISBN: 9783639491333 bzw. 3639491335, in Deutsch, AV Akademikerverlag, United States, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, The Book Depository EURO [60485773], London, United Kingdom.
Language: English Brand New Book ***** Print on Demand *****.Massively parallel sequencing technology has a wide range of applications. Its use in SNP detection is already widespread and promises results of high accuracy. The aim is to validate data generated with the Genome Analyser II. SNPs, detected by using different mapping and SNP estimation parameters implemented in the bioinformatics tool CLC were compared to SNPs that are detected by using the method of conventional Sanger sequencing. Lines of D. mauritiana were used. As reference genome in CLC I was bound to use the genome of D. simulans, because there is no available genome of D. mauritiana until now. Using a stringent parameter set (short parameter set) that allows few mismatches of reads when mapping against the reference genome, only few regions are recovered which show divergence to the reference. 60 -81 SNPs detected with this parameter set are false positive ones compared to Sanger sequencing. If a less stringent parameter set is used this results in a very high number of false positive SNPs. Two times more SNPs were recovered with this parameter set, thereof 70-80 are false positive ones. Based on my results I drew conclude that the best approach for SNP detection is to make one first run permitting a high number of mismatches. The next step should be the use of more stringent values to reduce the high number of false positive SNPs.
Language: English Brand New Book ***** Print on Demand *****.Massively parallel sequencing technology has a wide range of applications. Its use in SNP detection is already widespread and promises results of high accuracy. The aim is to validate data generated with the Genome Analyser II. SNPs, detected by using different mapping and SNP estimation parameters implemented in the bioinformatics tool CLC were compared to SNPs that are detected by using the method of conventional Sanger sequencing. Lines of D. mauritiana were used. As reference genome in CLC I was bound to use the genome of D. simulans, because there is no available genome of D. mauritiana until now. Using a stringent parameter set (short parameter set) that allows few mismatches of reads when mapping against the reference genome, only few regions are recovered which show divergence to the reference. 60 -81 SNPs detected with this parameter set are false positive ones compared to Sanger sequencing. If a less stringent parameter set is used this results in a very high number of false positive SNPs. Two times more SNPs were recovered with this parameter set, thereof 70-80 are false positive ones. Based on my results I drew conclude that the best approach for SNP detection is to make one first run permitting a high number of mismatches. The next step should be the use of more stringent values to reduce the high number of false positive SNPs.
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Validation of deep sequencing data from Drosophila mauritiana
~EN NW ABISBN: 9783639491333 bzw. 3639491335, vermutlich in Englisch, VDM Verlag Dr. Müller, Saarbrücken, Deutschland, neu, Hörbuch.
Lieferung aus: Österreich, Lieferzeit: 5 Tage, zzgl. Versandkosten.
Massively parallel sequencing technology has a wide range of applications. Its use in SNP detection is already widespread and promises results of high accuracy. The aim is to validate data generated with the Genome Analyser II. SNPs, detected by using different mapping and SNP estimation parameters implemented in the bioinformatics tool CLC were compared to SNPs that are detected by using the method of conventional Sanger sequencing. Lines of D. mauritiana were used. As reference genome in CLC I was bound to use the genome of D. simulans, because there is no available genome of D. mauritiana until now. Using a stringent parameter set (short parameter set) that allows few mismatches of reads when mapping against the reference genome, only few regions are recovered which show divergence to the reference. 60%-81% SNPs detected with this parameter set are false positive ones compared to Sanger sequencing. If a less stringent parameter set is used this results in a very high number of false positive SNPs. Two times more SNPs were recovered with this parameter set, thereof 70-80% are false positive ones. Based on my results I drew conclude that the best approach for SNP detection is to make one first run permitting a high number of mismatches. The next step should be the use of more stringent values to reduce the high number of false positive SNPs.
Massively parallel sequencing technology has a wide range of applications. Its use in SNP detection is already widespread and promises results of high accuracy. The aim is to validate data generated with the Genome Analyser II. SNPs, detected by using different mapping and SNP estimation parameters implemented in the bioinformatics tool CLC were compared to SNPs that are detected by using the method of conventional Sanger sequencing. Lines of D. mauritiana were used. As reference genome in CLC I was bound to use the genome of D. simulans, because there is no available genome of D. mauritiana until now. Using a stringent parameter set (short parameter set) that allows few mismatches of reads when mapping against the reference genome, only few regions are recovered which show divergence to the reference. 60%-81% SNPs detected with this parameter set are false positive ones compared to Sanger sequencing. If a less stringent parameter set is used this results in a very high number of false positive SNPs. Two times more SNPs were recovered with this parameter set, thereof 70-80% are false positive ones. Based on my results I drew conclude that the best approach for SNP detection is to make one first run permitting a high number of mismatches. The next step should be the use of more stringent values to reduce the high number of false positive SNPs.
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Validation of deep sequencing data from Drosophila mauritiana - by classic Sanger sequencing
~EN PB NWISBN: 9783639491333 bzw. 3639491335, vermutlich in Englisch, AV Akademikerverlag, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Validation of deep sequencing data from Drosophila mauritiana: Massively parallel sequencing technology has a wide range of applications. Its use in SNP detection is already widespread and promises results of high accuracy. The aim is to validate data generated with the Genome Analyser II. SNPs, detected by using different mapping and SNP estimation parameters implemented in the bioinformatics tool CLC were compared to SNPs that are detected by using the method of conventional Sanger sequencing. Lines of D. mauritiana were used. As reference genome in CLC I was bound to use the genome of D. simulans, because there is no available genome of D. mauritiana until now. Using a stringent parameter set (short parameter set) that allows few mismatches of reads when mapping against the reference genome, only few regions are recovered which show divergence to the reference. 60%-81% SNPs detected with this parameter set are false positive ones compared to Sanger sequencing. If a less stringent parameter set is used this results in a very high number of false positive SNPs. Two times more SNPs were recovered with this parameter set, thereof 70-80% are false positive ones. Based on my results I drew conclude that the best approach for SNP detection is to make one first run permitting a high number of mismatches. The next step should be the use of more stringent values to reduce the high number of false positive SNPs. Englisch, Taschenbuch.
Validation of deep sequencing data from Drosophila mauritiana: Massively parallel sequencing technology has a wide range of applications. Its use in SNP detection is already widespread and promises results of high accuracy. The aim is to validate data generated with the Genome Analyser II. SNPs, detected by using different mapping and SNP estimation parameters implemented in the bioinformatics tool CLC were compared to SNPs that are detected by using the method of conventional Sanger sequencing. Lines of D. mauritiana were used. As reference genome in CLC I was bound to use the genome of D. simulans, because there is no available genome of D. mauritiana until now. Using a stringent parameter set (short parameter set) that allows few mismatches of reads when mapping against the reference genome, only few regions are recovered which show divergence to the reference. 60%-81% SNPs detected with this parameter set are false positive ones compared to Sanger sequencing. If a less stringent parameter set is used this results in a very high number of false positive SNPs. Two times more SNPs were recovered with this parameter set, thereof 70-80% are false positive ones. Based on my results I drew conclude that the best approach for SNP detection is to make one first run permitting a high number of mismatches. The next step should be the use of more stringent values to reduce the high number of false positive SNPs. Englisch, Taschenbuch.
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Validation of deep sequencing data from Drosophila mauritiana (2013)
DE NWISBN: 9783639491333 bzw. 3639491335, in Deutsch, AV Akademikerverlag, neu.
Von Händler/Antiquariat, PBShop [61989342], Secaucus, NJ, U.S.A.
New Book. Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
New Book. Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Validation of Deep Sequencing Data from Drosophila Mauritiana (2014)
DE PB NWISBN: 9783639491333 bzw. 3639491335, in Deutsch, BLUES KIDS OF AMER 01/10/2014, Taschenbuch, neu.
Von Händler/Antiquariat, Books2Anywhere [190245], Fairford, GLO, United Kingdom.
New Book. Shipped from UK. This item is printed on demand.
New Book. Shipped from UK. This item is printed on demand.
7
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Validation of deep sequencing data from Drosophila mauritiana: by classic Sanger sequencing (2013)
DE PB NW RPISBN: 9783639491333 bzw. 3639491335, in Deutsch, AV Akademikerverlag, Taschenbuch, neu, Nachdruck.
Lieferung aus: Deutschland, Versandkostenfrei.
Von Händler/Antiquariat, English-Book-Service Mannheim [1048135], Mannheim, Germany.
This item is printed on demand for shipment within 3 working days.
Von Händler/Antiquariat, English-Book-Service Mannheim [1048135], Mannheim, Germany.
This item is printed on demand for shipment within 3 working days.
8
Validation of deep sequencing data from Drosophila mauritiana (2013)
~EN PB NWISBN: 9783639491333 bzw. 3639491335, vermutlich in Englisch, VDM Verlag Dr. Müller, Saarbrücken, Deutschland, Taschenbuch, neu.
Lieferung aus: Deutschland, Next Day, Versandkostenfrei.
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