AUC Estimation of Interval Censored Survival Data

Iterated Convex Minorant Algorithm for interval censored event data
Volkmar Henschel, Christiane Heiss, Ulrich Mansmann
Implementation of ICM-Algorithm by Wei Pan, J. Comp. & Gr. Stat. 78: 109-120, 1999
Algorithm for the Cox proportional hazard model for interval censored data

Iterated Convex Minorant Algorithm for interval censored event
data
Volkmar Henschel, Christiane Heiss, Ulrich Mansmann
<mansmann@ibe.med.uni-muenchen.de>
Implementation of ICM-Algorithm by Wei Pan, J. Comp. & Gr.
Stat. 78: 109-120, 1999 Algorithm for the Cox proportional
hazard model for interval censored data

Volkmar Henschel [aut, cre], Ulrich Mansmann [aut], Christiane
Heiss [ctb]

Volkmar Henschel<henschel@ibe.med.uni-muenchen.de>, Christiane Heiss<christiane.heiss@web.de>, Ulrich Mansmann <mansmann@ibe.med.uni-muenchen.de>

person("Yingwei", "Peng", role = c("aut", "cre"), email = "yingwei.peng@queensu.ca")
Mixture cure models with random effects to survival data as described in Peng and Taylor (2011) <doi:10.1002/sim.4098>.

Reconstruction of a Directed Acyclic Graph with Interventions
Provides intdag() for a constrained maximum likelihood estimate of a directed acyclic graph with intervention data. Also available is obsdag() for an estimate with observation data only, based on the method in the paper by Yuan, Shen and Pan (2018) <doi:10.1093/biomet/asy057>.

Integrative Analysis of RNA-Seq and ChIP-Seq Data
person(given = "Yingying",
family = "Cao",
role = c("aut", "cre"),
email = "yingying.cao@uni-due.de")
Integrative analysis of gene expression (RNA-Seq data), and histone
modification data for user-defined sets of histone marks (ChIP-Seq data) to
discover consistent changes in genes between biological conditions.
Additionally, Pareto optimization is used to prioritize genes based on the
level of consistent changes in both RNA-Seq and ChIP-Seq data.
GenomicRanges, GenomeInfoDb, IRanges, GenomicAlignments,
biomaRt, Rsamtools, rPref, DESeq2, apeglm

Integrative analysis of gene expression (RNA-Seq data), and histone
modification data for user-defined sets of histone marks (ChIP-Seq data) to
discover consistent changes in genes between biological conditions.
Additionally, Pareto optimization is used to prioritize genes based on the
level of consistent changes in both RNA-Seq and ChIP-Seq data.
Method is described in Cao, Y. et al. (2020) <doi:10.1186/s12864-020-07205-6>.