Cancer driver mutation prediction through Bayesian integration of multi-omic data

Hotspot mutations delineating diverse mutational signatures and biological utilities across cancer types

(2016) Tenghui Chen et al.   BMC GENOMICS

Transcriptomic Characterization of SF3B1 Mutation Reveals Its Pleiotropic Effects in Chronic Lymphocytic Leukemia

(2016) Lili Wang et al.   CANCER CELL

High-throughput Phenotyping of Lung Cancer Somatic Mutations

(2016) Alice H. Berger et al.   CANCER CELL

Role of non-coding sequence variants in cancer

(2016) Ekta Khurana et al.   NATURE REVIEWS GENETICS

Neomorphic mutations create therapeutic challenges in cancer

(2016) V Takiar et al.   ONCOGENE

Identification of Variant-Specific Functions of PIK3CA by Rapid Phenotyping of Rare Mutations

(2015) T. Dogruluk et al.   CANCER RESEARCH

Identifying recurrent mutations in cancer reveals widespread lineage diversity and mutational specificity

(2015) Matthew T Chang et al.   NATURE BIOTECHNOLOGY

Effect of predicted protein-truncating genetic variants on the human transcriptome

(2015) M. A. Rivas et al.   SCIENCE

Clonal status of actionable driver events and the timing of mutational processes in cancer evolution

(2015) Nicholas McGranahan et al.   Science Translational Medicine

Systematic analysis of somatic mutations impacting gene expression in 12 tumour types

(2015) Jiarui Ding et al.   Nature Communications

Combining gene mutation with gene expression data improves outcome prediction in myelodysplastic syndromes

(2015) Moritz Gerstung et al.   Nature Communications

Cancer-Associated SF3B1 Hotspot Mutations Induce Cryptic 3′ Splice Site Selection through Use of a Different Branch Point

(2015) Rachel B. Darman et al.   Cell Reports

A pan-cancer proteomic perspective on The Cancer Genome Atlas

(2014) Rehan Akbani et al.   Nature Communications

Analysis of Stop-Gain and Frameshift Variants in Human Innate Immunity Genes

(2014) Antonio Rausell et al.   PLoS Computational Biology

Mutational heterogeneity in cancer and the search for new cancer-associated genes

(2013) Michael S. Lawrence et al.   NATURE

CanDrA: Cancer-Specific Driver Missense Mutation Annotation with Optimized Features

(2013) Yong Mao et al.   PLoS One

Integrative Annotation of Variants from 1092 Humans: Application to Cancer Genomics

(2013) Ekta Khurana et al.   SCIENCE

Cancer Genome Landscapes

(2013) B. Vogelstein et al.   SCIENCE

DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer

(2013) Ali Bashashati et al.   GENOME BIOLOGY

MuSiC: Identifying mutational significance in cancer genomes

(2012) N. D. Dees et al.   GENOME RESEARCH

The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups

(2012) Christina Curtis et al.   NATURE

Circumventing Cancer Drug Resistance in the Era of Personalized Medicine

(2012) Levi A. Garraway et al.   Cancer Discovery

Correlation of Somatic Mutation and Expression Identifies Genes Important in Human Glioblastoma Progression and Survival

(2011) D. L. Masica et al.   CANCER RESEARCH

Hallmarks of Cancer: The Next Generation

(2011) Douglas Hanahan et al.   CELL

Prognostic significance of IDH-1 and MGMT in patients with glioblastoma: One step forward, and one step back?

(2011) Stephanie E Combs et al.   Radiation Oncology

A method and server for predicting damaging missense mutations

(2010) Ivan A Adzhubei et al.   NATURE METHODS

Pathway Commons, a web resource for biological pathway data

(2010) E. G. Cerami et al.   NUCLEIC ACIDS RESEARCH

ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data

(2010) K. Wang et al.   NUCLEIC ACIDS RESEARCH

Identifying a High Fraction of the Human Genome to be under Selective Constraint Using GERP++

(2010) Eugene V. Davydov et al.   PLoS Computational Biology

Cancer-Specific High-Throughput Annotation of Somatic Mutations: Computational Prediction of Driver Missense Mutations

(2009) H. Carter et al.   CANCER RESEARCH

The cancer genome

(2009) Michael R. Stratton et al.   NATURE

Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm

(2009) Prateek Kumar et al.   Nature Protocols

Learning a Prior on Regulatory Potential from eQTL Data

(2009) Su-In Lee et al.   PLoS Genetics