Title: Clustering of Genomic Regions Analysis Method
person("Seyed Ali", "Madani Tonekaboni", , email = "ali.madanitonekaboni@mail.utoronto.ca", role = c("aut")),
person("Victor", "Kofia", , email = "victor.kofia@uhnresearch.ca", role = c("aut")),
person("Mathieu", "Lupien", , email = "mlupien@uhnres.utoronto.ca", role = c("aut")),
person("Benjamin", "Haibe-Kains", , email = "benjamin.haibe.kains@utoronto.ca", role = c("aut", "cre"))
Description: Provides a new method for identification of clusters of genomic
regions within chromosomes. Primarily, it is used for calling clusters of
cis-regulatory elements (COREs). 'CREAM' uses genome-wide maps of genomic regions
in the tissue or cell type of interest, such as those generated from chromatin-based
assays including DNaseI, ATAC or ChIP-Seq. 'CREAM' considers proximity of the elements
within chromosomes of a given sample to identify COREs in the following steps:
1) It identifies window size or the maximum allowed distance between the elements
within each CORE, 2) It identifies number of elements which should be clustered
as a CORE, 3) It calls COREs, 4) It filters the COREs with lowest order which
does not pass the threshold considered in the approach.
Author: Seyed Ali Madani Tonekaboni [aut],

Title: Calibrated Ratio Estimator under Double Sampling Design
Authors@R: c(person("Dr. Sadikul", "Islam", role = c("aut","cre"), email = "sadikul.islamiasri@gmail.com"),person("Dr. Md", "Yeasin", role = "aut", email = "yeasin.iasri@gmail.com"),person("Dr. M.", "Muruganandam", role = "aut", email = "mail2mmm20@gmail.com"), person("Dr. M.", "Madhu ", role = "aut", email = "madhupmd@gmail.com"))
Maintainer: Dr. Sadikul Islam <sadikul.islamiasri@gmail.com>
Description: Population ratio estimator (calibrated) under two-phase random sampling design has gained enormous popularity in the recent time. This package provides functions for estimation population ratio (calibrated) under two phase sampling design, including the approximate variance of the ratio estimator. The improved ratio estimator can be applicable for both the case, when auxiliary data is available at unit level or aggregate level (eg., mean or total) for first phase sampled. Calibration weight of each unit of the second phase sample was calculated. Single and combined inclusion probabilities were also estimated for both phases under two phase random [simple random sampling without replacement (SRSWOR)] sampling. The improved ratio estimator's percentage coefficient of variation was also determined as a measure of accuracy. This package has been developed based on the theoretical development of Islam et al. (2021) and Ozgul (2020) <doi:10.1080/00949655.2020.1844702>.