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Articles 1 - 30 of 53
Full-Text Articles in Physical Sciences and Mathematics
A Statistical Framework For The Analysis Of Chip-Seq Data, Pei Fen Kuan, Dongjun Chung, Guangjin Pan, James A. Thomson, Ron Stewart, Sunduz Keles
A Statistical Framework For The Analysis Of Chip-Seq Data, Pei Fen Kuan, Dongjun Chung, Guangjin Pan, James A. Thomson, Ron Stewart, Sunduz Keles
Sunduz Keles
Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) has revolutionalized experiments for genome-wide profiling of DNA-binding proteins, histone modifications, and nucleosome occupancy. As the cost of sequencing is decreasing, many researchers are switching from microarray-based technologies (ChIP-chip) to ChIP-Seq for genome-wide study of transcriptional regulation. Despite its increasing and well-deserved popularity, there is little work that investigates and accounts for sources of biases in the ChIP-Seq technology. These biases typically arise from both the standard pre-processing protocol and the underlying DNA sequence of the generated data.
We study data from a naked DNA sequencing experiment, which sequences non-cross-linked DNA after deproteinizing and …
Integrative Analysis Of Cancer Genomic Data, Shuangge Ma
Integrative Analysis Of Cancer Genomic Data, Shuangge Ma
Shuangge Ma
In the past decade, we have witnessed a period of unparallel development in the field of cancer genomics. To address the same or similar biomedical questions, multiple cancer genomic studies have been independently designed and conducted. Cancer gene signatures identified from analysis of individual datasets often have low reproducibility. A cost-effective way of improving reproducibility is to conduct integrative analysis of datasets from multiple studies with comparable designs. To properly integrate multiple studies and conduct integrative analysis, we need to access various public data warehouses, retrieve experiment protocols and raw data, evaluate individual studies and select those with comparable designs, …
Marginal Hazards Model For Multivariate Failure Time Data With Auxiliary Covariates, Zhaozhi Fan, Xiao-Feng Wang
Marginal Hazards Model For Multivariate Failure Time Data With Auxiliary Covariates, Zhaozhi Fan, Xiao-Feng Wang
Xiaofeng Wang
A marginal hazards model of multivariate failure times has been developed based on the ‘working independence’ assumption [L.J. Wei, D.Y. Lin, and L. Wessfeld, Regression analysis of multivariate incomplete failure time data by modeling marginal distributions, J. Amer. Statist. Assoc. 84 (1989), pp. 1065–1073.]. In this article, we study the marginal hazards model of multivariate failure times with continuous auxiliary covariates. We consider the case of common baseline hazards for subjects from the same clusters. We extend the kernel smoothing procedure of Zhou and Wang [H. Zhou and C.Y. Wang, Failure time regression with continuous covariates measured with error, J. …
Identification Of Cancer-Associated Gene Pathways From Analysis Of Expression Data, Shuangge Ma
Identification Of Cancer-Associated Gene Pathways From Analysis Of Expression Data, Shuangge Ma
Shuangge Ma
No abstract provided.
Multiple Loci Within The Major Histocompatibility Complex Confer Risk Of Psoriasis, Bing-Jian Feng, Liang-Dan Sun, Razieh Soltani-Arabshahi, Anne M. Bowcock, Rajan P. Nair, Philip Stuart, James T. Elder, Steven J. Schrodi, Ann B. Begovich, Goncalo R. Abecasis, Xue-Jun Zhang, Kristina P. Callis Duffin, Gerald G. Krueger, David E. Goldgar
Multiple Loci Within The Major Histocompatibility Complex Confer Risk Of Psoriasis, Bing-Jian Feng, Liang-Dan Sun, Razieh Soltani-Arabshahi, Anne M. Bowcock, Rajan P. Nair, Philip Stuart, James T. Elder, Steven J. Schrodi, Ann B. Begovich, Goncalo R. Abecasis, Xue-Jun Zhang, Kristina P. Callis Duffin, Gerald G. Krueger, David E. Goldgar
Steven J Schrodi
Psoriasis is a common inflammatory skin disease characterized by thickened scaly red plaques. Previously we have performed a genome-wide association study (GWAS) on psoriasis with 1,359 cases and 1,400 controls, which were genotyped for 447,249 SNPs. The most significant finding was for SNP rs12191877, which is in tight linkage disequilibrium with HLA-Cw*0602, the consensus risk allele for psoriasis. However, it is not known whether there are other psoriasis loci within the MHC in addition to HLA-C. In the present study, we searched for additional susceptibility loci within the human leukocyte antigen (HLA) region through in-depth analyses of the GWAS data; …
Lecture 5, Shuangge Ma
Final Project, Shuangge Ma
Lecture 4, Shuangge Ma
Lecture 4, Shuangge Ma
Computer Intensive Methods Lecture 13, Shuangge Ma
Final Project (Description), Shuangge Ma
Final Project (Data), Shuangge Ma
Lecture 3, Shuangge Ma
Lecture 2, Shuangge Ma
Reference: Multiple Imputation, Shuangge Ma
Reference: Weighted Bootstrap, Shuangge Ma
Computer Intensive Methods Lecture 9, Shuangge Ma
Computer Intensive Methods Lecture 8, Shuangge Ma
Reference: Counter Examples [Bootstrap], Shuangge Ma
Reference: Counter Examples [Bootstrap], Shuangge Ma
Shuangge Ma
No abstract provided.
Computer Intensive Methods Lecture 7 (Lab 2), Shuangge Ma
Computer Intensive Methods Lecture 7 (Lab 2), Shuangge Ma
Shuangge Ma
No abstract provided.
Computer Intensive Methods Lecture 6, Shuangge Ma
Reference: Block Jackknife, Shuangge Ma
Computer Intensive Methods Lecture 5, Shuangge Ma
Reading: Simulate Multivariate Distribution, Shuangge Ma
Reading: Simulate Multivariate Distribution, Shuangge Ma
Shuangge Ma
No abstract provided.
Computer Intensive Methods Lecture 4, Shuangge Ma
Computer Intensive Methods Lecture 3 (Lab 1), Shuangge Ma
Computer Intensive Methods Lecture 3 (Lab 1), Shuangge Ma
Shuangge Ma
No abstract provided.
Computer Intensive Methods Lecture 2, Shuangge Ma
A Tale Of Two Streets: Incorporating Grouping Structure In High Dimensional Data Mining, Shuangge Ma
A Tale Of Two Streets: Incorporating Grouping Structure In High Dimensional Data Mining, Shuangge Ma
Shuangge Ma
No abstract provided.
Regression When The Predictors Are Images, Philip T. Reiss
Regression When The Predictors Are Images, Philip T. Reiss
Philip T. Reiss
No abstract provided.
Smoothing Parameter Selection For A Class Of Semiparametric Linear Models, Philip T. Reiss, R. Todd Ogden
Smoothing Parameter Selection For A Class Of Semiparametric Linear Models, Philip T. Reiss, R. Todd Ogden
Philip T. Reiss
Spline-based approaches to nonparametric and semiparametric regression, as well as to regression of scalar outcomes on functional predictors, entail choosing a parameter controlling the extent to which roughness of the fitted function is penalized. In this paper we demonstrate that the equations determining two popular methods for smoothing parameter selection, generalized cross-validation and restricted maximum likelihood, share a similar form that allows us to prove several results common to both, and to derive a condition under which they yield identical values. These ideas are illustrated by application of functional principal component regression, a method for regressing scalars on functions, to …