1. Introduction | 2. Installation | 3. Integration of dataset which includes only miRNA and gene expression values | 3.1. miRNA:target pairs | 3.2. Gene expression in normal and tumor samples | 3.3. miRNA expression data | 3.4. Integrating and analysing data | 3.5. The sum of two conditions: | 4. Dataset (huge_example) which includes miRNA and gene expressions and miRNA:target interaction factors | 4.1. Description of the huge_example dataset | 4.2. Select a node as trigger | 5. Finding perturbation efficiency on an experimental dataset | 6. Session Info | References
Package: ceRNAnetsim 1.25.0
Selcen Ari Yuka
ceRNAnetsim: Regulation Simulator of Interaction between miRNA and Competing RNAs (ceRNA)
This package simulates regulations of ceRNA (Competing Endogenous) expression levels after a expression level change in one or more miRNA/mRNAs. The methodolgy adopted by the package has potential to incorparate any ceRNA (circRNA, lincRNA, etc.) into miRNA:target interaction network. The package basically distributes miRNA expression over available ceRNAs where each ceRNA attracks miRNAs proportional to its amount. But, the package can utilize multiple parameters that modify miRNA effect on its target (seed type, binding energy, binding location, etc.). The functions handle the given dataset as graph object and the processes progress via edge and node variables.
Authors:
ceRNAnetsim_1.25.0.tar.gz
ceRNAnetsim_1.25.0.zip(r-4.7)ceRNAnetsim_1.25.0.zip(r-4.6)ceRNAnetsim_1.25.0.zip(r-4.5)
ceRNAnetsim_1.25.0.tgz(r-4.6-any)ceRNAnetsim_1.25.0.tgz(r-4.5-any)
ceRNAnetsim_1.25.0.tar.gz(r-4.7-any)ceRNAnetsim_1.25.0.tar.gz(r-4.6-any)
ceRNAnetsim_1.25.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ceRNAnetsim/json (API)
| # Install 'ceRNAnetsim' in R: |
| install.packages('ceRNAnetsim', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/selcenari/cernanetsim/issues
Datasets:
- huge_example - Huge example
- midsamp - Midsamp
- midsamp_new_counts - Midsamp_new_counts
- minsamp - Minsamp
- mirtarbasegene - Mirtarbasegene
- new_counts - New_counts
- TCGA_E9_A1N5_mirnanormal - TCGA_E9_A1N5_mirnanormal
- TCGA_E9_A1N5_mirnatumor - TCGA_E9_A1N5_mirnatumor
- TCGA_E9_A1N5_normal - TCGA_E9_A1N5_normal
- TCGA_E9_A1N5_tumor - TCGA_E9_A1N5_tumor
On BioConductor:ceRNAnetsim-1.25.0(bioc 3.24)ceRNAnetsim-1.24.0(bioc 3.23)
networkinferencesystemsbiologynetworkgraphandnetworktranscriptomicscernamirnanetwork-biologynetwork-simulatortcgatidygraphtidyverse
Last updated from:578c191f42. Checks:1 WARNING, 7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | WARNING | 174 | ||
| linux-devel-x86_64 | NOTE | 234 | ||
| source / vignettes | OK | 370 | ||
| linux-release-x86_64 | NOTE | 272 | ||
| macos-release-arm64 | NOTE | 109 | ||
| macos-oldrel-arm64 | NOTE | 123 | ||
| windows-devel | NOTE | 163 | ||
| windows-release | NOTE | 150 | ||
| windows-oldrel | NOTE | 140 | ||
| wasm-release | OK | 152 |
Exports:calc_perturbationfind_affected_nodesfind_iterationfind_node_perturbationfind_targeting_nodespriming_graphsimulatesimulate_visupdate_howupdate_nodesupdate_variablesvis_graph
Dependencies:base64enccachemclicodetoolscpp11digestdplyrfarverfastmapfurrrfuturegenericsggforceggplot2ggraphggrepelglobalsgluegraphlayoutsgridExtragtableigraphisobandjsonlitelabelinglatticelifecyclelistenvmagrittrMASSMatrixmemoiseparallellypillarpkgconfigpolyclippurrrR6RColorBrewerRcppRcppArmadillorlangS7scalesstringistringrsystemfontstibbletidygraphtidyrtidyselecttweenrutf8vctrsviridisviridisLitewithr
A TCGA dataset application
Last update: 2019-11-26
Started: 2019-03-18
The auxiliary commands which can help to the users
1. Introduction | 2. Installation | 3. Selection of perturbing element from dataset | 3.1. Selection of HIST1H3H gene at vignette How does the system behave in mirtarbase dataset without interaction factors? | 3.2. Selection of ACTB gene at vignette How does the system behave in mirtarbase dataset without interaction factors? | 4. Determination of ACTB gene perturbation efficiency with different expression level changes | 5. Session Info
Last update: 2019-11-26
Started: 2019-08-06
Calculating Number of Iterations Required to Reach Steady-State
1. Introduction | 2. Installation | 3. Comparison of gaining steady-state durations of middle and minimal datasets | 3.1. Suggestion for simulation iteration | 3.2. Find appropriate iteration number with find_iteration and then simulate accordingly | 4. What is perturbation efficiency? | 4.1. How does the calc_perturbation() work? | 4.2. A Short-cut: Finding perturbation efficiencies for whole nodes of network | 5. Session Info
Last update: 2019-11-25
Started: 2019-03-15
Basic Use of ceRNAnetsim
1. Introduction | 2. Installation | 3. About the data | 4. Simulation via expression values of miRNAs and genes in minsamp dataset | 4.1. Handle basic dataset | 4.2. Trigger a change | 4.3. Simulate the changes in graph | 4.4. A special case: knockdown | 5. Simulation via interaction factors in addition to expression values of miRNAs and genes in minsamp dataset | 5.1. Change expression level of one or more nodes in the graph | 5.2. Update the node variables with edge variables. | 5.3. Simulate the model | 5.4. Visualisation of the graph | 6. Session Info
Last update: 2019-11-24
Started: 2019-08-06
