Incomplete MaxSAT approaches for combinatorial testing

We present a Satisfiability (SAT)-based approach for building Mixed Covering Arrays with Constraints of minimum length, referred to as the Covering Array Number problem. This problem is central in Combinatorial Testing for the detection of system failures. In particular, we show how to apply Maximum Satisfiability (MaxSAT) technology by describing efficient encodings for different classes of complete and incomplete MaxSAT solvers to compute optimal and suboptimal solutions, respectively. Similarly, we show how to solve through MaxSAT technology a closely related problem, the Tuple Number problem, which we extend to incorporate constraints. For this problem, we additionally provide a new MaxSAT-based incomplete algorithm. The extensive experimental evaluation we carry out on the available Mixed Covering Arrays with Constraints benchmarks and the comparison with state-of-the-art tools confirm the good performance of our approaches.We would like to thank specially Akihisa Yamada for the access to several benchmarks for our experiments and for solving some questions about his previous work on Combinatorial Testing with Constraints. This work was partially supported by Grant PID2019-109137GB-C21 funded by MCIN/AEI/10.13039/501100011033, PANDEMIES 2020 by Agencia de Gestio d’Ajuts Universitaris i de Recerca (AGAUR), Departament d’Empresa i Coneixement de la Generalitat de Catalunya; FONDO SUPERA COVID-19 funded by Crue-CSIC-SANTANDER, ISINC (PID2019-111544GB-C21), and the MICNN FPU fellowship (FPU18/02929)

Determinacions del perfil genètic de tumors sòlids de l’adult

Perfil genètic; Tumors sòlids; Adults; PrecisióPerfil genético; Tumores sólidos; Adultos; PrecisiónGenetic profile; Solid tumors; Adults; AccuracyEn aquest estudi s’ha definit la llista de gens per a cada patologia i tots ells han estat seleccionats atenent a; la seva utilitat diagnòstica per definir els subtipus tumorals en localitzacions tumorals molt concretes; la seva utilitat pronòstica i predictiva, sempre que això comporti un canvi d’actitud terapèutica; la seva utilitat terapèutica per a la indicació de l’ús de fàrmacs diana

Determinacions del perfil genètic de tumors sòlids de l’adult

Perfil genètic; Tumors sòlids; Adults; PrecisióPerfil genético; Tumores sólidos; Adultos; PrecisiónGenetic profile; Solid tumors; Adults; AccuracyEn aquest estudi s’ha definit la llista de gens per a cada patologia i tots ells han estat seleccionats atenent a; la seva utilitat diagnòstica per definir els subtipus tumorals en localitzacions tumorals molt concretes; la seva utilitat pronòstica i predictiva, sempre que això comporti un canvi d’actitud terapèutica; la seva utilitat terapèutica per a la indicació de l’ús de fàrmacs diana

ICO-ICS Praxis para el tratamiento médico y con irradiación de cáncer colorrectal

Tractament mèdic; Tractament amb irradiació; Còlon; Recte; CàncerMedical treatment; Irradiation treatment; Colon; Rectum; CancerTratamiento médico; Tratamiento con irradiación; Colon; Recto; CáncerEl càncer de còlon i recte (CCR) és el més freqüent a Catalunya segons dades del Pla director d’oncologia estimades per a 2017. La incidència del CCR és superior en homes, amb un increment anual de l'1,3% en els homes i el 0,5% en les dones des de 1994. A Espanya, segons l’informe de la SEOM, que recull dades de la REDECAN, posiciona el CCR com un dels més freqüents i probables de diagnosticar el 2019, amb 44.937 nous casos. Segons les dades dels registres de GLOBOCAN 2018, el CCR és el segon càncer amb més incidència a Europa. La incidència distribuïda per sexes és del 16,7% en homes i del 13,3% en dones. Els objectius d'aquesta guia són: -Desenvolupar, difondre, implementar i avaluar resultats de la ICO-ICSPraxi de càncer colorectal. -Disminuir la variabilitat terapèutica entre els pacients tractats als diferents centres d'aquesta institució. -Implementar els resultats de la terapèutica en els pacients amb adenocarcinoma de pàncrees tractats d'acord amb les recomanacions d'aquesta guia

OptiLog V2: Model, Solve, Tune and Run

We present an extension of the OptiLog Python framework. We fully redesign the solvers module to support the dynamic loading of incremental SAT solvers with support for external libraries. We introduce new modules for modelling problems into Non-CNF format with support for Pseudo Boolean constraints, for evaluating and parsing the results of applications, and we add support for constrained execution of blackbox programs and SAT-heritage integration. All these enhancements allow OptiLog to become a swiss knife for SAT-based applications in academic and industrial environments

Exploiting Configurations of MaxSAT Solvers

In this paper, we describe how we can effectively exploit alternative parameter configurations to a MaxSAT solver. We describe how these configurations can be computed in the context of MaxSAT. In particular, we experimentally show how to easily combine configurations of a non-competitive solver to obtain a better solving approach

Incomplete MaxSAT approaches for combinatorial testing

We present a Satisfiability (SAT)-based approach for building Mixed Covering Arrays with Constraints of minimum length, referred to as the Covering Array Number problem. This problem is central in Combinatorial Testing for the detection of system failures. In particular, we show how to apply Maximum Satisfiability (MaxSAT) technology by describing efficient encodings for different classes of complete and incomplete MaxSAT solvers to compute optimal and suboptimal solutions, respectively. Similarly, we show how to solve through MaxSAT technology a closely related problem, the Tuple Number problem, which we extend to incorporate constraints. For this problem, we additionally provide a new MaxSAT-based incomplete algorithm. The extensive experimental evaluation we carry out on the available Mixed Covering Arrays with Constraints benchmarks and the comparison with state-of-the-art tools confirm the good performance of our approaches

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that -80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAFPeer reviewe

Sex differences in oncogenic mutational processes

Funder: Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada (NSERC Canadian Network for Research and Innovation in Machining Technology); doi: https://doi.org/10.13039/501100002790Funder: Genome Canada (Génome Canada); doi: https://doi.org/10.13039/100008762Funder: Canada Foundation for Innovation (Fondation canadienne pour l'innovation); doi: https://doi.org/10.13039/501100000196Funder: Terry Fox Research Institute (Institut de Recherche Terry Fox); doi: https://doi.org/10.13039/501100004376Abstract: Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here we report a pan-cancer analysis of sex differences in whole genomes of 1983 tumours of 28 subtypes as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in molecular cancer research