Nonparametric tests for longitudinal DNA copy number data

A New Nonparametric Regression for Longitudinal Data

In many area of medical research, a relation analysis between one response variable and some explanatory variables is desirable. Regression is the most common tool in this situation. If we have some assumptions for such normality for response variable, we could use it. In this paper we propose a nonparametric regression that does not have normality assumption for response variable and we focus ...

a new nonparametric regression for longitudinal data

in many area of medical research, a relation analysis between one response variable and some explanatory variables is desirable. regression is the most common tool in this situation. if we have some assumptions for such normality for response variable, we could use it. in this paper we propose a nonparametric regression that does not have normality assumption for response variable and we focus ...

Auc-based Tests for Nonparametric Functions with Longitudinal Data

Longitudinal data are very common in biomedical and clinical research, for example, CD4+ cell responses and viral load responses in AIDS clinical research. It is challenging to do inference for the whole trajectory of these longitudinal data if a parametric function is not available to model the trajectories. In this paper we develop an area-under-the-curve (AUC) based nonparametric method to c...

Framework for Identifying Common Aberrations in DNA Copy Number Data

High-resolution array comparative genomic hybridization (aCGH) provides exon-level mapping of DNA aberrations in cells or tissues. Such aberrations are central to carcinogenesis and, in many cases, central to targeted therapy of the cancers. Some of the aberrations are sporadic, one-of-a-kind changes in particular tumor samples; others occur frequently and reflect common themes in cancer biolog...

Statistical methods for DNA copy-number detection