Clare Pacini
Wellcome Trust Sanger Institute
25 Papers
36 Citations
Clare Pacini is an academic researcher from Wellcome Trust Sanger Institute. The author has contributed to research in topics: Computer science & Biology. The author has an hindex of 8, co-authored 20 publications. Previous affiliations of Clare Pacini include European Bioinformatics Institute & University of Cambridge.
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Papers
Integrated cross-study datasets of genetic dependencies in cancer.
Clare Pacini,Joshua M. Dempster,Isabella Boyle,Emanuel Gonçalves,Hanna Najgebauer,Hanna Najgebauer,Emre Karakoc,Dieudonne van der Meer,Andrew Barthorpe,Howard Lightfoot,Patricia Jaaks,James M. McFarland,Mathew J. Garnett,Aviad Tsherniak,Francesco Iorio +14 more
TL;DR: In this article, the authors integrated the two largest independent CRISPR-Cas9 screens performed to date (at the Broad and Sanger institutes) by assessing, comparing, and selecting methods for correcting biases due to heterogeneous single-guide RNA efficiency.
Agreement between two large pan-cancer CRISPR-Cas9 gene dependency data sets.
Joshua M. Dempster,Clare Pacini,Sasha Pantel,Fiona M. Behan,Thomas M Green,John M. Krill-Burger,Charlotte M. Beaver,Scott T. Younger,Victor A. Zhivich,Hanna Najgebauer,Felicity Allen,Emanuel Gonçalves,Rebecca Shepherd,John G. Doench,Kosuke Yusa,Kosuke Yusa,Francisca Vazquez,Leopold Parts,Leopold Parts,Jesse S. Boehm,Todd R. Golub,Todd R. Golub,William C. Hahn,William C. Hahn,David E. Root,Mathew J. Garnett,Aviad Tsherniak,Francesco Iorio +27 more
TL;DR: The authors show that the two largest independent CRISPR-Cas9 gene-dependency screens are concordant, paving the way for joint analysis of the data sets.
Integrated cross-study datasets of genetic dependencies in cancer
Clare Pacini,Joshua M. Dempster,Isabella Boyle,Emanuel Gonçalves,Hanna Najgebauer,Hanna Najgebauer,Emre Karakoc,Dieudonne van der Meer,Andrew Barthorpe,Howard Lightfoot,Patricia Jaaks,James M. McFarland,Mathew J. Garnett,Aviad Tsherniak,Francesco Iorio +14 more
TL;DR: The integrated datasets recapitulate findings from the individual ones, provide larger statistical power allowing novel cancer- and subtype-specific analyses, unveil additional biomarkers of gene dependency, and improve the detection of common essential genes.
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Agreement between two large pan-cancer CRISPR-Cas9 gene dependency datasets
Joshua M. Dempster,Clare Pacini,Sasha Pantel,Fiona M. Behan,Thomas M Green,John M. Krill-Burger,Charlotte M. Beaver,Victor A. Zhivich,Hanna Najgebauer,Felicity Allen,Emanuel Gonçalves,Rebecca Shepherd,John G. Doench,Kosuke Yusa,Francisca Vazquez,Leopold Parts,Jesse S. Boehm,Todd R. Golub,William C. Hahn,David E. Root,Mathew J. Garnett,Francesco Iorio,Aviad Tsherniak +22 more
TL;DR: It is found that batch effects are driven principally by two key experimental parameters: the reagent library and the assay length, which indicates that the Broad and Sanger CRISPR-Cas9 viability screens yield robust and reproducible findings.
DvD: An R/Cytoscape pipeline for drug repurposing using public repositories of gene expression data.
Clare Pacini,Francesco Iorio,Emanuel Gonçalves,Murat Iskar,Thomas Klabunde,Peer Bork,Julio Saez-Rodriguez +6 more
TL;DR: Drug versus Disease provides a pipeline, available through R or Cytoscape, for the comparison of drug and disease gene expression profiles from public microarray repositories, which can be used to generate hypotheses of drug-repurposing and to infer side effects of drugs.