multistateQTL

Summarize and visualize multi-state QTL data

https://github.com/dunstone-a/multistateqtl

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Repository

Summarize and visualize multi-state QTL data

Basic Info
  • Host: GitHub
  • Owner: dunstone-a
  • Language: R
  • Default Branch: devel
  • Homepage:
  • Size: 188 KB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 2 years ago · Last pushed 12 months ago
Metadata Files
Readme Changelog

README.md

multistateQTL R Package

multistateQTL is an R package for applying basic statistical tests, summarizing, and visualizing QTL summary statistics from multiple states (e.g., tissues, celltypes, environmental conditions). It works on the QTLExperiment (QTLE) object class (available in Bioconductor, QTLExperiment), where rows represent features (e.g., genes, transcripts, genomic regions), columns represent states, and assays are the various summary statistics.

Installation and Usage

To install from GitHub, use devtools:

install.packages("devtools") devtools::install_git("https://github.com/dunstone-a/multistateQTL.git", build_vignettes = TRUE)

From Bioconductor, use:

``` if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager")

BiocManager::install("multistateQTL") ```

Using the most recent version of R is strongly recommended (R 4.4 at the time of writing).

There are several other packages from CRAN and Bioconductor that multistateQTL uses, so you will need to have these packages installed as well. The CRAN packages should install automatically when multistateQTL is installed, but you will need to install the Bioconductor packages manually.

It is also necessary to install the package QTLExperiment.

QTLExperiment

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

BiocManager::install("QTLExperiment") ```

Getting started

Get started with multistateQTL by checking out the vignette. From inside an R session, load multistateQTL and then browse the vignettes:

library(multistateQTL) browseVignettes("multistateQTL")

There is a detailed HTML document available that introduces the main features and functionality of multistateQTL.

Planned package additions

Here is a running list of features that we plan to add to the multistateQTL package:

  • Global and feature-wise FDR correction of p-values assay
  • conditional FDR (cFDR)

Disclaimer

The package is currently in a Beta state. The major functionality of the package is settled, but it is still under development so may change from time to time. Please do try it and contact me with bug reports, feedback, feature requests, questions and suggestions to improve the package.

Written by Christina Brady Del Azodi, November 2022. Revised by Amelia Dunstone, April 2024

Owner

  • Name: Millie
  • Login: dunstone-a
  • Kind: user

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Last synced: 11 months ago

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Top Authors
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  • MichaelChirico (1)
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Packages

  • Total packages: 1
  • Total downloads:
    • bioconductor 3,480 total
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 4
  • Total maintainers: 1
bioconductor.org: multistateQTL

Toolkit for the analysis of multi-state QTL data

  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 3,480 Total
Rankings
Dependent repos count: 0.0%
Average: 15.6%
Dependent packages count: 31.3%
Maintainers (1)
Last synced: 11 months ago

Dependencies

DESCRIPTION cran
  • ComplexHeatmap * depends
  • QTLExperiment * depends
  • SummarizedExperiment * depends
  • collapse * depends
  • data.table * depends
  • S4Vectors * imports
  • circlize * imports
  • dplyr * imports
  • fitdistrplus * imports
  • ggplot2 * imports
  • grDevices * imports
  • grid * imports
  • mashr * imports
  • matrixStats * imports
  • methods * imports
  • stats * imports
  • tidyr * imports
  • viridis * imports
  • BiocStyle * suggests
  • covr * suggests
  • knitr * suggests
  • rmarkdown * suggests
  • testthat * suggests