RT Journal Article SR Electronic T1 FIREWORKS: a bottom-up approach to integrative coessentiality network analysis JF Life Science Alliance JO Life Sci. Alliance FD Life Science Alliance LLC SP e202000882 DO 10.26508/lsa.202000882 VO 4 IS 2 A1 Amici, David R A1 Jackson, Jasen M A1 Truica, Mihai I A1 Smith, Roger S A1 Abdulkadir, Sarki A A1 Mendillo, Marc L YR 2021 UL https://www.life-science-alliance.org/content/4/2/e202000882.abstract AB Genetic coessentiality analysis, a computational approach which identifies genes sharing a common effect on cell fitness across large-scale screening datasets, has emerged as a powerful tool to identify functional relationships between human genes. However, widespread implementation of coessentiality to study individual genes and pathways is limited by systematic biases in existing coessentiality approaches and accessibility barriers for investigators without computational expertise. We created FIREWORKS, a method and interactive tool for the construction and statistical analysis of coessentiality networks centered around gene(s) provided by the user. FIREWORKS incorporates a novel bias reduction approach to reduce false discoveries, enables restriction of coessentiality analyses to custom subsets of cell lines, and integrates multiomic and drug–gene interaction datasets to investigate and target contextual gene essentiality. We demonstrate the broad utility of FIREWORKS through case vignettes investigating gene function and specialization, indirect therapeutic targeting of “undruggable” proteins, and context-specific rewiring of genetic networks.