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nempi

Nested Effects Models based Perturbation Inference - https://doi.org/10.1093/bioinformatics/btab113 - https://bioconductor.org/packages/nempi

https://github.com/cbg-ethz/nempi

Science Score: 57.0%

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
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    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    2 of 4 committers (50.0%) from academic institutions
  • ✓
    Institutional organization owner
    Organization cbg-ethz has institutional domain (www.bsse.ethz.ch)
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (5.8%) to scientific vocabulary

Keywords from Contributors

bioconductor-package gene genomics sequencing ontology grna-sequence immune-repertoire proteomics
Last synced: 6 months ago · JSON representation

Repository

Nested Effects Models based Perturbation Inference - https://doi.org/10.1093/bioinformatics/btab113 - https://bioconductor.org/packages/nempi

Basic Info
Statistics
  • Stars: 2
  • Watchers: 2
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Created over 6 years ago · Last pushed 11 months ago
Metadata Files
Readme

README.md

Introduction

If many genes are perturbed in a population of cells, this can lead to diseases like cancer. The perturbations can happen in different ways, e.g. via mutations, copy number abberations or methylation. However, not all perturbations are observed in all samples.

Nested Effects Model-based perturbation inference (NEM$\pi$) uses observed perturbation profiles and gene expression data to infer unobserved perturbations and augment observed ones. The causal network of the perturbed genes (P-genes) is modelled as an adjacency matrix $\phi$ and the genes with observed gene expression (E-genes) are modelled with the attachment $\theta$ with $\theta_{ij}=1$, if E-gene $j$ is attached to S-gene $i$. If E-gene $j$ is attached to P-gene $i$, $j$ shows an effect for a perturbation of P-gene $i$. Hence, $\phi\theta$ predicts gene expression profiles, which can be compared to the real data. NEM$\pi$ iteratively infers a network $\phi$ based on gene expression profiles and a perturbation profile, and the perturbation profile based on a network $\phi$.

Install:

```{r} if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager")

BiocManager::install("nempi") ```

Most recent (devel) version:

```r install.packages("devtools")

library(devtools)

install_github("cbg-ethz/nempi")

library(nempi) ``` For the reproduction of the publication see the script in the other directory.

Reference

Pirkl M, Beerenwinkel N (2021). "Inferring perturbation profiles of cancer samples." Bioinformatics. https://doi.org/10.1093/bioinformatics/btab113.

Owner

  • Name: Computational Biology Group (CBG)
  • Login: cbg-ethz
  • Kind: organization
  • Location: Basel, Switzerland

Beerenwinkel Lab at ETH Zurich

GitHub Events

Total
  • Push event: 2
Last Year
  • Push event: 2

Committers

Last synced: 10 months ago

All Time
  • Total Commits: 49
  • Total Committers: 4
  • Avg Commits per committer: 12.25
  • Development Distribution Score (DDS): 0.429
Past Year
  • Commits: 4
  • Committers: 1
  • Avg Commits per committer: 4.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
mpirkl m****l@b****h 28
J Wokaty j****y@s****u 10
Nitesh Turaga n****a@g****m 6
mpirkl m****l@y****e 5
Committer Domains (Top 20 + Academic)
yahoo.de: 1 sph.cuny.edu: 1 bsse.ethz.ch: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 2
  • Total pull requests: 0
  • Average time to close issues: 28 days
  • Average time to close pull requests: N/A
  • Total issue authors: 2
  • Total pull request authors: 0
  • Average comments per issue: 10.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 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
  • axeljeremy7 (1)
  • HenrikBengtsson (1)
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • bioconductor 7,120 total
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 5
  • Total maintainers: 1
bioconductor.org: nempi

Inferring unobserved perturbations from gene expression data

  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 7,120 Total
Rankings
Dependent repos count: 0.0%
Dependent packages count: 0.0%
Forks count: 18.4%
Average: 26.9%
Stargazers count: 29.0%
Downloads: 87.1%
Maintainers (1)
martinpirkl@yahoo.de
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 4.1 depends
  • mnem * depends
  • e1071 * imports
  • epiNEM * imports
  • graphics * imports
  • matrixStats * imports
  • naturalsort * imports
  • nnet * imports
  • randomForest * imports
  • stats * imports
  • utils * imports
  • BiocGenerics * suggests
  • BiocStyle * suggests
  • RUnit * suggests
  • knitr * suggests
  • rmarkdown * suggests