Title: Meta-Analysis with Mean Differences
a research synthesis with mean difference data. One of the
unique features of this package is in its integration of
user-friendly functions to complete all statistical steps
involved in a meta-analysis with mean differences. It uses

a research synthesis with mean differences data. One of the
user-friendly functions to complete most of the statistical
steps involved in a meta-analysis with mean differences. It
uses recommended procedures as described in The Handbook of
Research Synthesis and Meta-Analysis (Cooper, Hedges, &

user-friendly functions to facilitate statistical analyses at
each stage in a meta-analysis with mean differences. It uses

Description: This is an integrated meta-analysis package for conducting	a research synthesis with mean differences data. One of the unique	features of this package is in its integration of user-friendly 	functions to facilitate statistical analyses at each stage in a meta-analysis with mean differences. It uses recommended procedures as	described in The 	Handbook of Research Synthesis and Meta-Analysis	(Cooper, Hedges, & Valentine, 2009).

Description: A collection of functions for conducting a meta-analysis with mean differences data.  It uses recommended procedures as	described in The 	Handbook of Research Synthesis and Meta-Analysis	(Cooper, Hedges, & Valentine, 2009).

Title: Tools for Normalizing and Comparing ChIP-seq Samples
Authors@R: person("Shiqi", "Tu", email = "tushiqi@picb.ac.cn",
Description: Chromatin immunoprecipitation followed by high-throughput
sequencing (ChIP-seq) is the premier technology for profiling genome-wide
localization of chromatin-binding proteins, including transcription
factors and histones with various modifications.
This package provides a robust method for normalizing ChIP-seq
signals across individual samples or groups of samples. It also designs
a self-contained system of statistical models for calling differential
ChIP-seq signals between two or more biological conditions as well as
for calling hypervariable ChIP-seq signals across samples. Refer to
Imports: stats, graphics, methods, locfit (>= 1.5.9), scales (>=
Suggests: gplots (>= 3.0.1), DescTools (>= 0.99.24), knitr, rmarkdown
Packaged: 2021-09-10 11:31:42 UTC; Administrator
Author: Shiqi Tu [aut, cre] (<https://orcid.org/0000-0003-3534-5714>)