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scDecouple: decoupling cellular response from infected proportion bias in scCRISPR-seq.
Meng, Qiuchen; Wei, Lei; Ma, Kun; Shi, Ming; Lin, Xinyi; Ho, Joshua W K; Li, Yinqing; Zhang, Xuegong.
  • Meng Q; MOE Key Lab of Bioinformatics & Bioinformatics Division BRNIST, Department of Automation, Tsinghua University, Beijing 100084, China.
  • Wei L; MOE Key Lab of Bioinformatics & Bioinformatics Division BRNIST, Department of Automation, Tsinghua University, Beijing 100084, China.
  • Ma K; School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
  • Shi M; Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Hong Kong SAR, China.
  • Lin X; MOE Key Lab of Bioinformatics & Bioinformatics Division BRNIST, Department of Automation, Tsinghua University, Beijing 100084, China.
  • Ho JWK; School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
  • Li Y; Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Hong Kong SAR, China.
  • Zhang X; School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
Brief Bioinform ; 25(2)2024 Jan 22.
Article en En | MEDLINE | ID: mdl-38324621
ABSTRACT
Single-cell clustered regularly interspaced short palindromic repeats-sequencing (scCRISPR-seq) is an emerging high-throughput CRISPR screening technology where the true cellular response to perturbation is coupled with infected proportion bias of guide RNAs (gRNAs) across different cell clusters. The mixing of these effects introduces noise into scCRISPR-seq data analysis and thus obstacles to relevant studies. We developed scDecouple to decouple true cellular response of perturbation from the influence of infected proportion bias. scDecouple first models the distribution of gene expression profiles in perturbed cells and then iteratively finds the maximum likelihood of cell cluster proportions as well as the cellular response for each gRNA. We demonstrated its performance in a series of simulation experiments. By applying scDecouple to real scCRISPR-seq data, we found that scDecouple enhances the identification of biologically perturbation-related genes. scDecouple can benefit scCRISPR-seq data analysis, especially in the case of heterogeneous samples or complex gRNA libraries.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Ensayos Analíticos de Alto Rendimiento / ARN Guía de Sistemas CRISPR-Cas Idioma: En Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Ensayos Analíticos de Alto Rendimiento / ARN Guía de Sistemas CRISPR-Cas Idioma: En Año: 2024 Tipo del documento: Article