Xianlong Wang

TL;DR: It is demonstrated that proteogenomic analysis of breast cancer elucidates functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

TL;DR: Peptide measurements in breast cancer cell lines were able to discriminate among molecular subtypes and identify genome-driven changes in the cancer proteome, establishing the feasibility of a large-scale effort to develop an MRM assay resource.

TL;DR: It is shown that deregulation of cyclin E causes human mammary epithelial cells to enter into mitosis with short unreplicated genomic segments at a small number of specific loci, leading to anaphase anomalies and ultimately deletions, demonstrating how oncogene-induced replication stress contributes to genomic instability in human cancer.

TL;DR: Competing methods for detecting interactions in genome wide association studies are compared and informative characteristics of various methods are revealed that are helpful to GWAS investigators.

TL;DR: A new method- mixEMM- is introduced for analyzing iTRAQ/TMT data with batch effects and batch-level nonignorable missingness and it is shown that, compared with existing approaches that utilize relative abundances and ignore the missing batches under the missing-completely-at-random assumption, the mix EMM method achieves more accurate parameter estimation and inference.