Raphael A Fraser,Stuart R Lipsitz,Debajyoti Sinha et al.
Raphael A Fraser et al.
There is a great need for statistical methods for analyzing skewed responses in complex sample surveys. Quantile regression is a logical option in addressing this problem but is often accompanied by incorrect variance estimation. We show ho...
Doubly robust nonparametric instrumental variable estimators for survival outcomes [0.03%]
生存结果的双重稳健非参数工具变量估计器
Youjin Lee,Edward H Kennedy,Nandita Mitra
Youjin Lee
Instrumental variable (IV) methods allow us the opportunity to address unmeasured confounding in causal inference. However, most IV methods are only applicable to discrete or continuous outcomes with very few IV methods for censored surviva...
Yiqun T Chen,Sean W Jewell,Daniela M Witten
Yiqun T Chen
In recent years, a number of methods have been proposed to estimate the times at which a neuron spikes on the basis of calcium imaging data. However, quantifying the uncertainty associated with these estimated spikes remains an open problem...
Prognosis of cancer survivors: estimation based on differential equations [0.03%]
癌症幸存者的预后：基于微分方程的估计
Pål C Ryalen,Bjørn Møller,Christoffer H Laache et al.
Pål C Ryalen et al.
We present a method for estimating several prognosis parameters for cancer survivors. The method utilizes the fact that these parameters solve differential equations driven by cumulative hazards. By expressing the parameters as solutions to...
Interpretable principal component analysis for multilevel multivariate functional data [0.03%]
多层次多变量功能数据的可解释主成分分析
Jun Zhang,Greg J Siegle,Tao Sun et al.
Jun Zhang et al.
Many studies collect functional data from multiple subjects that have both multilevel and multivariate structures. An example of such data comes from popular neuroscience experiments where participants' brain activity is recorded using moda...
Accounting for technical noise in Bayesian graphical models of single-cell RNA-sequencing data [0.03%]
单细胞RNA序列数据贝叶斯图形模型中技术噪声的考量
Jihwan Oh,Changgee Chang,Qi Long
Jihwan Oh
Single-cell RNA-sequencing (scRNAseq) data contain a high level of noise, especially in the form of zero-inflation, that is, the presence of an excessively large number of zeros. This is largely due to dropout events and amplification biase...
Assessing chromatin relocalization in 3D using the patient rule induction method [0.03%]
利用患者规则诱导法评估三维基因组中的染色质重新定位效应
Mark R Segal
Mark R Segal
Three-dimensional (3D) genome architecture is critical for numerous cellular processes, including transcription, while certain conformation-driven structural alterations are frequently oncogenic. Inferring 3D chromatin configurations has be...
Feature selection for support vector regression using a genetic algorithm [0.03%]
基于遗传算法的支持向量回归的特征选择方法研究
Shannon B McKearnan,David M Vock,G Elisabeta Marai et al.
Shannon B McKearnan et al.
Support vector regression (SVR) is particularly beneficial when the outcome and predictors are nonlinearly related. However, when many covariates are available, the method's flexibility can lead to overfitting and an overall loss in predict...
Theresa A Alexander,Rafael A Irizarry,Héctor Corrada Bravo
Theresa A Alexander
High-dimensional biological data collection across heterogeneous groups of samples has become increasingly common, creating high demand for dimensionality reduction techniques that capture underlying structure of the data. Discovering low-d...
Predicting the onset of breast cancer using mammogram imaging data with irregular boundary [0.03%]
基于不规则边界的乳腺X线影像数据的乳腺癌发病预测
Shu Jiang,Jiguo Cao,Graham A Colditz et al.
Shu Jiang et al.
With mammography being the primary breast cancer screening strategy, it is essential to make full use of the mammogram imaging data to better identify women who are at higher and lower than average risk. Our primary goal in this study is to...