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IntOMICS

IntOMICSr: an R package for integrative analysis of multi-omics data to infer regulatory networks.

https://github.com/anna-pacinkova/intomicsr

Science Score: 23.0%

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    CITATION.cff file
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    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
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    1 of 3 committers (33.3%) from academic institutions
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    Scientific vocabulary similarity
    Low similarity (11.1%) to scientific vocabulary

Keywords from Contributors

bioconductor-package gene grna-sequence immune-repertoire genomics ontology sequencing
Last synced: 11 months ago · JSON representation

Repository

IntOMICSr: an R package for integrative analysis of multi-omics data to infer regulatory networks.

Basic Info
  • Host: GitHub
  • Owner: anna-pacinkova
  • Language: R
  • Default Branch: devel
  • Homepage:
  • Size: 19.5 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 1
  • Releases: 0
Created almost 4 years ago · Last pushed about 2 years ago
Metadata Files
Readme Changelog

README.md

IntOMICSr: an R package for integrative analysis of multi-omics data to infer regulatory networks.

IntOMICSr is an efficient integrative framework based on Bayesian networks. IntOMICSr systematically analyses gene expression (GE), DNA methylation (METH), copy number variation (CNV) and biological prior knowledge (B) to infer regulatory networks. IntOMICSr complements the missing biological prior knowledge by so-called empirical biological knowledge (empB), estimated from the available experimental data. An automatically tuned MCMC algorithm (Yang and Rosenthal, 2017) estimates model parameters and the empirical biological knowledge. Conventional MCMC algorithm with additional Markov blanket resampling (MBR) step (Su and Borsuk, 2016) infers resulting regulatory network structure consisting of three types of nodes: GE nodes refer to gene expression levels, CNV nodes refer to associated copy number variations, and METH nodes refer to associated DNA methylation probe(s).

IntOMICSr takes as input: * gene expression matrix (required), * associated copy number variation matrix sampled from the same individuals (optional), * associated DNA methylation matrix of beta-values sampled from the same individuals (optional), and * the biological prior knowledge with information on known interactions among molecular features (optional, highly recommended).

The resulting regulatory network structure contains the edge weights $w_i$ representing the empirical frequency of given edge over samples of network structures from two independent MCMC simulations.

IntOMICSr framework

For further details about the IntOMICSr algorithm, its performance and benchmark analysis, see manuscript Pacinkova & Popovici, 2022.

Installation

```ruby

bioconductor install

if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("IntOMICSr")

install the newest (development) version from GitHub

install.packages("remotes")

remotes::install_github("anna-pacinkova/IntOMICSr") ```

Owner

  • Login: anna-pacinkova
  • Kind: user

GitHub Events

Total
  • Issues event: 1
Last Year
  • Issues event: 1

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 80
  • Total Committers: 3
  • Avg Commits per committer: 26.667
  • Development Distribution Score (DDS): 0.05
Past Year
  • Commits: 10
  • Committers: 3
  • Avg Commits per committer: 3.333
  • Development Distribution Score (DDS): 0.4
Top Committers
Name Email Commits
anna-pacinkova a****a@g****m 76
J Wokaty j****y@s****u 2
J Wokaty j****y 2
Committer Domains (Top 20 + Academic)
sph.cuny.edu: 1

Issues and Pull Requests

Last synced: about 1 year ago

All Time
  • Total issues: 1
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 1
  • Total pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • vamikakarn (1)
  • clauswilke (1)
Pull Request Authors
Top Labels
Issue Labels
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Packages

  • Total packages: 1
  • Total downloads:
    • bioconductor 1,070 total
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 3
  • Total maintainers: 1
bioconductor.org: IntOMICS

Integrative analysis of multi-omics data to infer regulatory networks

  • Versions: 3
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 1,070 Total
Rankings
Dependent repos count: 0.0%
Dependent packages count: 0.0%
Forks count: 19.8%
Average: 29.5%
Stargazers count: 33.2%
Downloads: 94.7%
Maintainers (1)
ana.pacinkova@gmail.com
Last synced: about 1 year ago

Dependencies

DESCRIPTION cran
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