Project description:We have combined a machine-learning approach with other strategies to optimize the efficiency of sgRNAs for CRISPR screens and have constructed a genome-wide, sequence-verified, arrayed CRISPR library. This incorporates expression strategies to facilitate multiplexed or combinatorial screening. By conducting parallel loss-of-function screens, we compare our approach to existing sgRNA design and expression strategies.
Project description:We have combined a machine-learning approach with other strategies to optimize the efficiency of sgRNAs for CRISPR screens and have constructed a genome-wide, sequence-verified, arrayed CRISPR library. This incorporates expression strategies to facilitate multiplexed or combinatorial screening. By conducting parallel loss-of-function screens, we compare our approach to existing sgRNA design and expression strategies.
Project description:We have combined a machine-learning approach with other strategies to optimize the efficiency of sgRNAs for CRISPR screens and have constructed a genome-wide, sequence-verified, arrayed CRISPR library. This incorporates expression strategies to facilitate multiplexed or combinatorial screening. By conducting parallel loss-of-function screens, we compare our approach to existing sgRNA design and expression strategies.
Project description:Genome-wide CRISPR-Cas9 knockout screen using TKOv1 sgRNA library was performed in isogenic RBM10-proficient and RBM10-deficient HCC827 cells.
