Title |
Enabling multiplexed testing of pooled donor cells through whole-genome sequencing
|
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Published in |
Genome Medicine, April 2018
|
DOI | 10.1186/s13073-018-0541-6 |
Pubmed ID | |
Authors |
Yingleong Chan, Ying Kai Chan, Daniel B. Goodman, Xiaoge Guo, Alejandro Chavez, Elaine T. Lim, George M. Church |
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/. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 5 | 22% |
United Kingdom | 4 | 17% |
Ecuador | 1 | 4% |
Canada | 1 | 4% |
Mexico | 1 | 4% |
Spain | 1 | 4% |
Unknown | 10 | 43% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 13 | 57% |
Scientists | 10 | 43% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 31 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 8 | 26% |
Researcher | 6 | 19% |
Student > Master | 4 | 13% |
Student > Doctoral Student | 3 | 10% |
Other | 3 | 10% |
Other | 2 | 6% |
Unknown | 5 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 8 | 26% |
Biochemistry, Genetics and Molecular Biology | 7 | 23% |
Medicine and Dentistry | 3 | 10% |
Immunology and Microbiology | 2 | 6% |
Neuroscience | 2 | 6% |
Other | 4 | 13% |
Unknown | 5 | 16% |