Rui Liu

TL;DR: PennCNV, a hidden Markov model (HMM) based approach, is presented for kilobase-resolution detection of CNVs from Illumina high-density SNP genotyping data, demonstrating the feasibility of whole-genome fine-mapping ofCNVs via high- density SNP genotypesing.

TL;DR: A scalable approach to sequence and quantify RNA molecules in isolated neuronal nuclei from a postmortem brain, generating 3227 sets of single-neuron data from six distinct regions of the cerebral cortex demonstrates a robust and scalable method for identifying and categorizing single nuclear transcriptomes.

TL;DR: In this paper, a model-free method to detect early warning signals of critical transitions, even with only a small number of samples, was proposed. And the authors theoretically derive an index based on a dynamical network biomarker (DNB) that serves as a general early warning signal indicating an imminent bifurcation or sudden deterioration before the critical transition occurs.

TL;DR: A model-free method to detect early-warning signals of critical transitions of complex diseases, even with only a small number of samples is developed, and it is shown that predicting a sudden transition from small samples is achievable provided that there are a large number of measurements for each sample, e.g., high-throughput data.

TL;DR: The authors developed pathway and gene set overdispersion analysis (PAGODA) to resolve multiple, potentially overlapping aspects of transcriptional heterogeneity by testing gene sets for coordinated variability among measured cells.