Efficient algorithms to discover alterations with complementary functional association in cancer

Recent large cancer studies have measured somatic alterations in an unprecedented number of tumours. These large datasets allow the identification of cancer-related sets of genetic alterations by identifying relevant combinatorial patterns. Among such patterns, mutual exclusivity has been employed by several recent methods that have shown its effectivenes in characterizing gene sets associated to cancer. Mutual exclusivity arises because of the complementarity, at the functional level, of alterations in genes which are part of a group (e.g., a pathway) performing a given function. The availability of quantitative target profiles, from genetic perturbations or from clinical phenotypes, provides additional information that can be leveraged to improve the identification of cancer related gene sets by discovering groups with complementary functional associations with such targets. In this work we study the problem of finding groups of mutually exclusive alterations associated with a quantitative (functional) target. We propose a combinatorial formulation for the problem, and prove that the associated computation problem is computationally hard. We design two algorithms to solve the problem and implement them in our tool UNCOVER. We provide analytic evidence of the effectiveness of UNCOVER in finding high-quality solutions and show experimentally that UNCOVER finds sets of alterations significantly associated with functional targets in a variety of scenarios. In addition, our algorithms are much faster than the state-of-the-art, allowing the analysis of large datasets of thousands of target profiles from cancer cell lines. We show that on one such dataset from project Achilles our methods identify several significant gene sets with complementary functional associations with targets.Comment: Accepted at RECOMB 201

A split-beam probe-pump-probe scheme for femtosecond time resolved protein X-ray crystallography

In order to exploit the femtosecond pulse duration of X-ray Free-Electron Lasers (XFEL) operating in the hard X-ray regime for ultrafast time-resolved protein crystallography experiments, critical parameters that determine the crystallographic signal-to-noise (I/σI) must be addressed. For single-crystal studies under low absorbed dose conditions, it has been shown that the intrinsic pulse intensity stability as well as mode structure and jitter of this structure, significantly affect the crystallographic signal-to-noise. Here, geometrical parameters are theoretically explored for a three-beam scheme: X-ray probe, optical pump, X-ray probe (or “probe-pump-probe”) which will allow experimental determination of the photo-induced structure factor amplitude differences, ΔF, in a ratiometric manner, thereby internally referencing the intensity noise of the XFEL source. In addition to a non-collinear split-beam geometry which separates un-pumped and pumped diffraction patterns on an area detector, applying an additional convergence angle to both beams by focusing leads to integration over mosaic blocks in the case of well-ordered stationary protein crystals. Ray-tracing X-ray diffraction simulations are performed for an example using photoactive yellow protein crystals in order to explore the geometrical design parameters which would be needed. The specifications for an X-ray split and delay instrument that implements both an offset angle and focused beams are discussed, for implementation of a probe-pump-probe scheme at the European XFEL. We discuss possible extension of single crystal studies to serial femtosecond crystallography, particularly in view of the expected X-ray damage and ablation due to the first probe pulse