sigident (!!! under development !!!)

This is the repository of the R package 'sigident'. It provides core functionalities to identify diagnostic and prognostic signatures from gene expression datasets.

Currently implemented features are:

• merging of microarray datasets (via the R package sigident.preproc)
• DEG analysis and functional analysis (via the R package sigident.func)
• Identification and validation of diagnostic signatures, using
  • Lasso regression
  • Elastic net regression
  • glmnet (grid search for best alpha and lambda)
• Identification of prognostic signatures

Installation

You can install sigident with the following commands in R:

install.packages("remotes")
remotes::install_github("kapsner/sigident")

The version of the package, which was used for the publication A Toolbox for Functional Analysis and the Systematic Identification of Diagnostic and Prognostic Gene Expression Signatures Combining Meta-Analysis and Machine Learning can anytime be reproduced using the version tag v0.0.2 during the installation process:

devtools::install_github("miracum/clearly-sigident", ref = "v0.0.2")

Example

Please view the package's vignette to see a detailled description how to prepare datasets in order to be suitable for usage with the sigident package and to learn, how to perform merging, signature and functional analyses of microarray data.

Since the building the package vignette takes rather long (~ 40 min.), we provide the already built vignettes in this repository.

Notice

The sigident package is under active development and not on CRAN yet - this means, that from time to time, the API can break, due to extending and modifying its functionality. It can also happen, that previoulsy included functions and/or function arguments are no longer supported. However, a detailed package vignette will be provided alongside with every major change in order to describe the currently supported workflow.

Citation

To cite the 'sigident' package in publications, please use:

@Article{,
    title = {A Toolbox for Functional Analysis and the Systematic Identification of Diagnostic and Prognostic Gene Expression Signatures Combining Meta-Analysis and Machine Learning},
    volume = {11},
    doi = {10.3390/cancers11101606},
    pages = {14},
    number = {1606},
    journal = {Cancers},
    author = {Johannes Vey and Lorenz A. Kapsner and Maximilian Fuchs and Philipp Unberath and Giulia Veronesi and Meik Kunz},
    year = {2019},
}

and

@Manual{,
    title = {sigident: Signature Analyses in Genomic Expression Sets},
    author = {Lorenz A. Kapsner and Johannes Vey and Meik Kunz and Andreas Pittroff},
    year = {2019},
    note = {R package version 0.0.1.9000},
    url = {https://gitlab.miracum.org/clearly/sigident},
}

More Infos:

• about CLEARLY: https://www.transcanfp7.eu/index.php/abstract/clearly.html
• about MIRACUM: https://www.miracum.org/
• about the Medical Informatics Initiative: https://www.medizininformatik-initiative.de/index.php/de