Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
DNA intelligence, and particularly the inference of biogeographical ancestry (BGA) is increasing in interest, and relevance within the forensic genetics community. The majority of current MPS-based forensic ancestry-informative assays focus on the differentiation of major global populations. The recently published MAPlex (Multiplex for the Asia Pacific) panel contains 144 SNPs and 20 microhaplotypes and aims to improve the differentiation of populations in the Asia Pacific region. This study reports the first forensic evaluation of the MAPlex panel using AmpliSeq technology and Ion S5 sequencing. This study reports on the overall performance of MAPlex including the assay's sequence coverage distribution and stability, baseline noise and description of problematic SNPs. Dilution series, artificially degraded and mixed DNA samples were also analysed to evaluate the sensitivity of the panel with challenging or compromised forensic samples. As the first panel to combine biallelic SNPs, multiple-allele SNPs and microhaplotypes, the MAPlex assay demonstrated an enhanced capacity for mixture detection, not easily performed with common binary SNPs. This performance evaluation indicates that MAPlex is a robust, stable and highly sensitive assay that is applicable to forensic casework for the prediction of BGA.
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Source |
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http://dx.doi.org/10.1016/j.fsigen.2020.102344 | DOI Listing |
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