Science Score: 39.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 3 DOI reference(s) in README -
○Academic publication links
-
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (11.9%) to scientific vocabulary
Repository
Bayesian Network Analysis of Intracranial Aneurysm
Basic Info
- Host: GitHub
- Owner: hirsch-lab
- License: cc-by-4.0
- Language: R
- Default Branch: main
- Size: 102 MB
Statistics
- Stars: 2
- Watchers: 0
- Forks: 0
- Open Issues: 1
- Releases: 0
Metadata Files
README.md
bnaiaR
Bayesian Network Analysis of Intracranial Aneurysm. Data preparation and analysis of risk factors for intracranial aneurysms.
Installation
You can install the released version of bnaiaR from Github with:
r
devtools::install_github("matteodelucchi/bnaiaR")
In case of installation issues caused by the package igraph, check this post:
github.com/igraph
To ensure smooth compatibility and to remain your local setup untouched, I recommend to use this package within a virtual environment from renv.
A local installation of mcmcabn was used,which can be installed withrenv` following this guide.
Description
Data
There are different data sets attached to the package. For example, the preprocessed raw data can be accessed with this command.
r
data(adb)
The data sets description can be accessed in the respective help page.
r
help(adb)
To follow the data preparation and more details consider the vignettes in this order:
- rawdataharmonization: Querying the raw data from a private
data base resulting in the
adb.rawdata set. - data_preprocessing: From raw data to the preprocessed
adbdata set. - datapreparationfor_experiments: Implementation of prior knowledge
(blacklist, banned-matrix), specification of variable distributions and
variable selection for each analysis scenario.
- correlation_analysis: Descriptive statistics.
- regression_analysis: Multivariable logistic regression models.
- Discrete BN structure learning: Structure learning for discrete BNs.
- DBN validation: Classification error estimation and inference.
ABN analysis: Structure learning was performed on a high-performance computing cluster followed by local postprocessing Details from additive BNs.
For the publication additional figures and tables were produced.
Citations
If you make use of this R package or one of its data sets in your research we would appreciate a citation of the following article:
Matteo Delucchi, Georg R. Spinner, Marco Scutari, Philippe Bijlenga, Sandrine Morel, Christoph M. Friedrich, Reinhard Furrer and Sven Hirsch. 2022. Bayesian network analysis reveals the interplay of intracranial aneurysm rupture risk factors. Computers in Biology and Medicine. 10.1016/j.compbiomed.2022.105740.
you can get it as BibTeX entry with
r
citation("bnaiaR")
Owner
- Name: Digital Health Group
- Login: hirsch-lab
- Kind: organization
- Location: Wädenswil, Switzerland
- Website: https://www.zhaw.ch/en/lsfm/institutes-centres/icls/computational-health/
- Repositories: 9
- Profile: https://github.com/hirsch-lab
Tools developed by the Computational Health Group, lead by Prof. Dr. Sven Hirsch.
GitHub Events
Total
Last Year
Dependencies
- R >= 3.5.0 depends
- RMariaDB * imports
- abn * imports
- bnlearn * imports
- caret * imports
- data.table * imports
- dplyr * imports
- forcats * imports
- ggplot2 * imports
- lubridate * imports
- magrittr * imports
- purrr * imports
- stringr * imports
- tidyr * imports
- tidyselect * imports
- BiocManager * suggests
- ROCR * suggests
- Rgraphviz * suggests
- correlationfunnel * suggests
- cowplot * suggests
- kableExtra * suggests
- knitr * suggests
- pROC * suggests
- pscl * suggests
- rmarkdown * suggests
- sjPlot * suggests
- survAUC * suggests
- survival * suggests
- survminer * suggests