Identifying the Pathways Regulated by LncRNA Sets of Interest
Identifies pathways synergisticly regulated by the interested lncRNA(long non-coding RNA) sets based on a lncRNA-mRNA(messenger RNA) interaction network. 1) The lncRNA-mRNA interaction network was built from the protein-protein interactions and the lncRNA-mRNA co-expression relationships in 28 RNA-Seq data sets. 2) The interested lncRNAs can be mapped into networks as seed nodes and a random walk strategy will be performed to evaluate the rate of each coding genes influenced by the seed lncRNAs. 3) Pathways regulated by the lncRNA set will be evaluated by a weighted Kolmogorov-Smirnov statistic as an ES Score. 4) The p value and false discovery rate value will also be calculated through a permutation analysis. 5) The running score of each pathway can be plotted and the heat map of each pathway can also be plotted if an expression profile is provided. 6) The rank and scores of the gene list of each pathway can be printed.

Prioritizing Candidate LncRNAs Based on a Composite Multi-Level
Network
Prioritizing the disease lncRNAs based on random walking on a composite Multi-level network.

Generalized Spline Mixed Effect Models for Longitudinal Breath
Data
c( person("Anne-Christin", "Hauschild", email = "achauschild@googlemail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7499-4373")),
person("Sandy", "P. Eckel", role = c("ths", "com")),
person("Jan", "Baumbach", role = "ths"))
Automated analysis and modeling of longitudinal 'omics' data (e.g. breath 'metabolomics') using generalized spline mixed effect models. Including automated filtering of noise parameters and determination of breakpoints.
methods, lawstat, nlme, graphics, RColorBrewer, stats, base,
grDevices, qpdf
Anne-Christin Hauschild [aut, cre]
(<https://orcid.org/0000-0002-7499-4373>),
Sandy P. Eckel [ths, com],
Jan Baumbach [ths]

Functions for Performing Local FDR Estimation when Null and
Alternative are Poisson
person("Kris", "Sankaran", , "kriss1@stanford.edu", role = c("aut", "cre"))
The main idea of the Local FDR algorithm is to estimate both proportion of null observations and the ratio of null and alternative densities. In the case that there are many null observations, this can be done reliably, through maximum likelihood or generalized linear models. This package implements this in the case that the null and alternative densities are Poisson.