Inferring Shared Modules from Multiple Gene Expression Datasets
with Partially Overlapping Gene Sets
A method to infer modules of co-expressed genes and the
dependencies among the modules from multiple expression datasets that may
contain different sets of genes. Please refer to: Extracting a low-dimensional
description of multiple gene expression datasets reveals a potential driver for
tumor-associated stroma in ovarian cancer, Safiye Celik, Benjamin A. Logsdon,
Stephanie Battle, Charles W. Drescher, Mara Rendi, R. David Hawkins and Su-In
Lee (2016) <DOI:10.1186/s13073-016-0319-7>.

Quantify and Control Reproducibility in High-Throughput
Experiments
c( person(given="Yi",family="Zhao",role=c("aut"),email="zhayi@umich.edu"),
person(given="Xiaoquan",family="Wen",role=c("aut"),email="xqwen@umich.edu"),
person(given="Michael",family="Kleinsasser",role=c("cre"),email="mkleinsa@umich.edu")
)
Estimate the proportions of the null and the reproducibility and
non-reproducibility of the signal group for the input data set. The Bayes factor
calculation and EM (Expectation Maximization) algorithm procedures are also
included.
Yi Zhao [aut],
Xiaoquan Wen [aut],
Michael Kleinsasser [cre]

Hao Wang [cre, aut],
Diederick Vermetten [aut],
Carola Doerr [aut],
Thomas Bäck [aut]
c(
person("Hao", "Wang", email = "h.wang@liacs.leidenuniv.nl", role = c("cre","aut")),
person("Diederick", "Vermetten", email="d.vermetten@gmail.com", role = "aut"),
person("Carola", "Doerr", email = "Carola.Doerr@mpi-inf.mpg.de", role = "aut"),
person("Thomas", "Bäck", email="t.h.w.baeck@liacs.leidenuniv.nl", role = "aut"))
The data analysis module for the Iterative Optimization Heuristics
Profiler ('IOHprofiler'). This module provides statistical analysis methods for the
benchmark data generated by optimization heuristics, which can be visualized through a
web-based interface. The benchmark data is usually generated by the
experimentation module, called 'IOHexperimenter'. 'IOHanalyzer' also supports
the widely used 'COCO' (Comparing Continuous Optimisers) data format for benchmarking.
Rcpp, magrittr, dplyr, reshape2, data.table, ggplot2, plotly,
colorspace, colorRamps, RColorBrewer, shiny, shinyjs,
shinydashboard, markdown, DBI, dbplyr, withr