Publication: Enabling multiplexed testing of pooled donor cells through whole-genome sequencing
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Date
2018
Published Version
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BioMed Central
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Citation
Chan, Yingleong, Ying Kai Chan, Daniel B. Goodman, Xiaoge Guo, Alejandro Chavez, Elaine T. Lim, and George M. Church. 2018. “Enabling multiplexed testing of pooled donor cells through whole-genome sequencing.” Genome Medicine 10 (1): 31. doi:10.1186/s13073-018-0541-6. http://dx.doi.org/10.1186/s13073-018-0541-6.
Research Data
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/ Electronic supplementary material The online version of this article (10.1186/s13073-018-0541-6) contains supplementary material, which is available to authorized users.
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Keywords
Multiplexed testing, Barcode free method, Single nucleotide polymorphisms, Expectation maximization algorithm, Next-generation sequencing, Personal Genome Project
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