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. 2022 Dec 14;13:7748. doi: 10.1038/s41467-022-35378-z

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 2 — a Stacked barplot indicating the frequencies of 84 mutated driver genes across different cancer types. The number of mutated cell lines of a given cancer type may have an impact on the statistical power of the SLIdR framework. b Bubble-plot summarizing the significance (-log10(p-value)) of different driver genes (x-axis) pairing with the same SL partner gene (y-axis) as predicted by SLIdR in the pan-cancer analysis after filtering out false positives from multiple testing. The p-values are computed using one-sided IH-test. c Corresponding list of significant SL pairs after accounting for confounding mutations and performing causal inference using matching-based potential outcome models. d Differential sensitivities of pan-cancer SL pairs in subsets of cell lines grouped by primary sites (y-axis). Each panel corresponds to a specific driver gene (x-axis top) and encapsulates the significance profiles of all its SL-partners (x-axis bottom) across various primary sites. Each column in a given panel depicts the significance profile of the SL pair in subsets of cell lines grouped by primary sites. The p-values are computed using one-sided IH-test.