کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6553784 | 160893 | 2015 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
NOCIt: A computational method to infer the number of contributors to DNA samples analyzed by STR genotyping
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
بیوشیمی، ژنتیک و زیست شناسی مولکولی
ژنتیک
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: NOCIt: A computational method to infer the number of contributors to DNA samples analyzed by STR genotyping NOCIt: A computational method to infer the number of contributors to DNA samples analyzed by STR genotyping](/preview/png/6553784.png)
چکیده انگلیسی
Repetitive sequences in the human genome called short tandem repeats (STRs) are used in human identification for forensic purposes. Interpretation of DNA profiles generated using STRs is often problematic because of uncertainty in the number of contributors to the sample. Existing methods to identify the number of contributors work on the number of peaks observed and/or allele frequencies. We have developed a computational method called NOCIt that calculates the a posteriori probability (APP) on the number of contributors. NOCIt works on single source calibration data consisting of known genotypes to compute the APP for an unknown sample. The method takes into account signal peak heights, population allele frequencies, allele dropout and stutter-a commonly occurring PCR artifact. We tested the performance of NOCIt using 278 experimental and 40 simulated DNA mixtures consisting of one to five contributors with total DNA mass from 0.016 to 0.25Â ng. NOCIt correctly identified the number of contributors in 83% of the experimental samples and in 85% of the simulated mixtures, while the accuracy of the best pre-existing method to determine the number of contributors was 72% for the experimental samples and 73% for the simulated mixtures. Moreover, NOCIt calculated the APP for the true number of contributors to be at least 1% in 95% of the experimental samples and in all the simulated mixtures.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Forensic Science International: Genetics - Volume 16, May 2015, Pages 172-180
Journal: Forensic Science International: Genetics - Volume 16, May 2015, Pages 172-180
نویسندگان
Harish Swaminathan, Catherine M. Grgicak, Muriel Medard, Desmond S. Lun,