Package: dcanr 1.21.0
Dharmesh D. Bhuva
dcanr: Differential co-expression/association network analysis
This package implements methods and an evaluation framework to infer differential co-expression/association networks. Various methods are implemented and can be evaluated using simulated datasets. Inference of differential co-expression networks can allow identification of networks that are altered between two conditions (e.g., health and disease).
Authors:
dcanr_1.21.0.tar.gz
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dcanr.pdf |dcanr.html✨
dcanr/json (API)
NEWS
| # Install 'dcanr' in R: |
| install.packages('dcanr', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/davislaboratory/dcanr/issues
- sim102 - Simulated expression data with knock-outs
On BioConductor:dcanr-1.21.0(bioc 3.20)dcanr-1.20.0(bioc 3.19)
Last updated 2 months agofrom:d9e562e2b8
Exports:cor.pairsdcAdjustdcEvaluatedcMethodsdcNetworkdcPipelinedcScoredcTestdcZscoregetConditionNamesgetSimDatagetTrueNetworkmi.apperfMethodsperformanceMeasureplotSimNetwork
Dependencies:circlizeclicodetoolscolorspacecpp11digestdoRNGforeachGlobalOptionsglueigraphiteratorslatticelifecyclemagrittrMatrixpkgconfigplyrRColorBrewerRcppreshape2rlangrngtoolsshapestringistringrvctrs
Performing differential co-expression analysis using dcanr
Rendered fromdcanr_vignette.Rmdusingknitr::rmarkdownon Jun 30 2024.Last update: 2019-04-18
Started: 2018-10-05
Evaluating differential co-expression methods using dcanr
Rendered fromdcanr_evaluation_vignette.Rmdusingknitr::rmarkdownon Jun 30 2024.Last update: 2019-08-06
Started: 2018-10-05
