Discussion References

Time: Tuesday 6:30 - 8:30 (10-12)

Room: 四教307


Reading papers and books


MuSiC: Identifying mutational significance in cancer genomes

A Landscape of Driver Mutations in Melanoma (InVEx algorithm)

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

Discovery and prioritization of somatic mutations in diffuse large B-cell lymphoma (DLBCL) by whole-exome sequencing

CanPredict: a computational tool for predicting cancer-associated missense mutations

Distinguishing Cancer-Associated Missense Mutations from Common Polymorphisms

PANTHER: a library of protein families and subfamilies indexed by function

Human genomic disease variants: A neutral evolutionary explanation

A general framework for estimating the relative pathogenicity of human genetic variants

Copy number related

GISTIC           GISTIC 2.0

A scale-space method for detecting recurrent DNA copy number changes with analytical false discovery rate control

STAC: A method for testing the significance of DNA copy number aberrations across multiple array-CGH experiments

CGARS: cancer genome analysis by rank sums

A genomic random interval model for statistical analysis of genomic lesion data

Detection of candidate tumor driver genes using a fully integrated Bayesian approach

Integrative approach

An Integrated Approach to Uncover Drivers of Cancer

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

Efficient methods for identifying mutated driver pathways in cancer

ResponseNet: revealing signaling and regulatory networks linking genetic and transcriptomic screening data

Empirical process
Reference book1
Referecne book2