Title: Segment-Based Ordinary Kriging and Segment-Based Regression
Description: Segment-based Kriging methods, including segment-based ordinary
Kriging (SOK) and segment-based regression Kriging (SRK) for
spatial prediction of line segment spatial data as described in
spatial prediction and spatial visualisation. The descriptions of
the methods and case datasets refer to the citation information
Imports: stats, graphics, rgeos, RColorBrewer, sp, GD, rtop, FitAR,

Title: SNP-set (Sequence) Kernel Association Test
Author: Seunggeun Lee, Larisa Miropolsky and Micheal Wu
Packaged: 2012-05-11 15:13:23 UTC; seunggeun

Packaged: 2012-06-26 18:44:15 UTC; seunggeun

Author: Seunggeun (Shawn) Lee, with contributions from Larisa Miropolsky and Michael Wu
Description: SKAT is a kernel regression based association test between a set of single nucleotide polymorphism (SNP) and dichotomous or quantitative phenotypes. SKAT aggregates individual score test statistics of SNPs in a SNP set and efficiently computes SNP-set level p-values, while adjusting for covariates, such as principal components to account for population stratification.

Title: SNP-Set (Sequence) Kernel Association Test
Description: Functions for kernel regression based association tests including Burden test, SKAT and SKAT-O. These methods aggregate individual SNP score statistics in a SNP set and efficiently computes SNP-set level p-values, while adjusting for covariates.

Description: Functions for kernel-regression-based association tests including Burden test, SKAT and SKAT-O. These methods aggregate individual SNP score statistics in a SNP set and efficiently compute SNP-set level p-values.

Author: Seunggeun (Shawn) Lee and Zhangchen Zhao, with contributions from Larisa Miropolsky and Michael Wu

Authors@R: c(person("Seunggeun (Shawn)", "Lee", role = c("aut", "cre", "cph"), email = "lee7801@snu.ac.kr"),
person("Zhangchen", "Zhao", role = c("aut")),
person("Larisa", "Miropolsky", role = c("aut")),
person("Michael", "Wu", role = c("aut")))
Description: Functions for kernel-regression-based association tests including Burden test, SKAT and SKAT-O. These methods aggregate individual SNP score statistics in a SNP set and efficiently compute SNP-set level p-values. Methods  available in this package include SKAT described in Micheal Wu, Seunggeun Lee et al. (2011) <doi:10.1016/j.ajhg.2011.05.029>, SKAT-O in Seunggeun Lee et al. (2012) <doi:10.1093/biostatistics/kxs014>, combined test of rare and common variants in Iuliana Ionita-Laza and Seunggeun Lee et al. (2013) <doi:10.1016/j.ajhg.2013.04.015>, efficient resampling for binary traits in Seunggeun Lee et al. (2016) <doi:10.1093/biostatistics/kxv033>, and robust test for binary traits in Zhangchen Zhao et al. (2020) <doi:10.1016/j.ajhg.2019.11.012>.
Depends: R (>= 2.13.0), Matrix, SPAtest, RSpectra
Author: Seunggeun (Shawn) Lee [aut, cre, cph],