| Literature DB >> 31359007 |
Ryan T Leenay1, Amirali Aghazadeh2, Joseph Hiatt3,4,5,6,7, David Tse2, Theodore L Roth4, Ryan Apathy4, Eric Shifrut4, Judd F Hultquist7,8,9,10, Nevan Krogan7,8,9, Zhenqin Wu11, Giana Cirolia1, Hera Canaj1, Manuel D Leonetti1, Alexander Marson12,13,14,15,16,17, Andrew P May18,19, James Zou20,21,22.
Abstract
Understanding of repair outcomes after Cas9-induced DNA cleavage is still limited, especially in primary human cells. We sequence repair outcomes at 1,656 on-target genomic sites in primary human T cells and use these data to train a machine learning model, which we have called CRISPR Repair Outcome (SPROUT). SPROUT accurately predicts the length, probability and sequence of nucleotide insertions and deletions, and will facilitate design of SpCas9 guide RNAs in therapeutically important primary human cells.Entities:
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Year: 2019 PMID： 31359007 PMCID： PMC7388783 DOI： 10.1038/s41587-019-0203-2
Source DB: PubMed Journal: Nat Biotechnol ISSN： 1087-0156 Impact factor: 54.908