Package: iBMQ 1.47.0
Greg Imholte
iBMQ: integrated Bayesian Modeling of eQTL data
integrated Bayesian Modeling of eQTL data
Authors:
iBMQ_1.47.0.tar.gz
iBMQ_1.47.0.zip(r-4.5)iBMQ_1.47.0.zip(r-4.4)iBMQ_1.47.0.zip(r-4.3)
iBMQ_1.47.0.tar.gz(r-4.5-noble)iBMQ_1.47.0.tar.gz(r-4.4-noble)
iBMQ_1.47.0.tgz(r-4.4-emscripten)iBMQ_1.47.0.tgz(r-4.3-emscripten)
iBMQ.pdf |iBMQ.html✨
iBMQ/json (API)
| # Install 'iBMQ' in R: |
| install.packages('iBMQ', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- PPA.liver - A matrix with Posterior Probabilities of Association
- gene - Gene expression from whole eye tissue from n = 68 BXD RIS mice.
- genepos - Gene position data frame
- genotype.liver - A set of 290 SNPs from 60 F2 mice.
- map.liver - SNP position data frame
- phenotype.liver - Gene expression from liver tissue from n = 60 F2 mice.
- probe.liver - Gene position data frame
- snp - A set of 1700 SNP from 68 BXD RIS mice.
- snppos - SNP position data frame
On BioConductor:iBMQ-1.47.0(bioc 3.21)iBMQ-1.46.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
microarraypreprocessinggeneexpressionsnpgslopenmp
Last updated 2 months agofrom:f5a261f11f. Checks:OK: 1 NOTE: 4. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 29 2024 |
| R-4.5-win-x86_64 | NOTE | Nov 29 2024 |
| R-4.5-linux-x86_64 | NOTE | Nov 29 2024 |
| R-4.4-win-x86_64 | NOTE | Nov 29 2024 |
| R-4.3-win-x86_64 | NOTE | Nov 29 2024 |
Exports:calculateThresholdeqtlClassifiereqtlFindereqtlMcmchotspotFinder
Dependencies:BiobaseBiocGenericsclicolorspacefansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| iBMQ : An Integrated Hierarchical Bayesian Model for Multivariate eQTL Mapping | iBMQ-package iBMQ |
| Calculate PPA significance threshold leading to a desired false discovery rate | calculateThreshold |
| Classifying the eQTLs | eqtlClassifier |
| eqtlFinder | eqtlFinder |
| Bayesian Multiple eQTL mapping using MCMC | eqtlMcmc |
| Gene expression from whole eye tissue from n = 68 BXD RIS mice. | gene |
| Gene position data frame | genepos |
| A set of 290 SNPs from 60 F2 mice. | genotype.liver |
| hotspotFinder | hotspotFinder |
| SNP position data frame | map.liver |
| Gene expression from liver tissue from n = 60 F2 mice. | phenotype.liver |
| A matrix with Posterior Probabilities of Association | PPA.liver |
| Gene position data frame | probe.liver |
| A set of 1700 SNP from 68 BXD RIS mice. | snp |
| SNP position data frame | snppos |