Enabling multiplexed testing of pooled donor cells through whole-genome sequencing

Autor:	Yingleong Chan, Ying Kai Chan, Daniel B. Goodman, Xiaoge Guo, Alejandro Chavez, Elaine T. Lim, George M. Church
Jazyk:	angličtina
Rok vydání:	2018
Předmět:	Multiplexed testing Barcode free method Single nucleotide polymorphisms Expectation maximization algorithm Next-generation sequencing Personal Genome Project Medicine Genetics QH426-470
Zdroj:	Genome Medicine, Vol 10, Iss 1, Pp 1-11 (2018)
Druh dokumentu:	article
ISSN:	1756-994X
DOI:	10.1186/s13073-018-0541-6
Popis:	Abstract We describe a method that enables the multiplex screening of a pool of many different donor cell lines. Our method accurately predicts each donor proportion from the pool without requiring the use of unique DNA barcodes as markers of donor identity. Instead, we take advantage of common single nucleotide polymorphisms, whole-genome sequencing, and an algorithm to calculate the proportions from the sequencing data. By testing using simulated and real data, we showed that our method robustly predicts the individual proportions from a mixed-pool of numerous donors, thus enabling the multiplexed testing of diverse donor cells en masse. More information is available at https://pgpresearch.med.harvard.edu/poolseq/
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/91ce078fac0a446897ce139106322d9d Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
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