chevreulShiny
Interactive exploratory data analysis of full-length scRNA-seq as SingleCellExperiments
Science Score: 26.0%
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Low similarity (15.7%) to scientific vocabulary
Last synced: 9 months ago
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Repository
Interactive exploratory data analysis of full-length scRNA-seq as SingleCellExperiments
Basic Info
- Host: GitHub
- Owner: cobriniklab
- License: mit
- Language: R
- Default Branch: master
- Homepage: https://cobriniklab.github.io/chevreulShiny/
- Size: 184 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 2
Created over 1 year ago
· Last pushed 12 months ago
Metadata Files
Readme
Changelog
Contributing
License
Code of conduct
Support
README.Rmd
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
eval = FALSE,
collapse = TRUE,
comment = "#>",
dpi = 900,
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# chevreulShiny
This package includes a set of Shiny apps for exploring single cell RNA datasets processed as a SingleCellExperiment
A demo using a human gene transcript dataset from Shayler et al. (link) is available here
There are also convenient functions for:
- Clustering and Dimensional Reduction of Raw Sequencing Data.
- Integration and Label Transfer
- Louvain Clustering at a Range of Resolutions
- Cell cycle state regression and labeling
> [!WARNING]
> chevreulShiny was designed for full-length smart-seq based single cell data. Default settings may not be appropriate for droplet (10x) data, though most can be adjusted. Keep in mind best practices regarding normalization, dimensional reduction, etc. when using.
## Installation
You can install the released version of chevreulShiny from github with:
### Install locally and run in three steps:
You can install chevreulShiny locally using the following steps:
```{r, eval=FALSE}
install.packages("devtools")
devtools::install_github("cobriniklab/chevreulShiny")
library(chevreulShiny)
create_project_db()
```
You can also customize the location of the app using these steps:
```{r, eval=FALSE}
devtools::install_github("cobriniklab/chevreulShiny")
library(chevreulShiny)
create_project_db(destdir = "/your/path/to/app")
```
## TLDR
chevreulShiny provides a single command to:
- construct a SingleCellExperiment object
- filter genes by minimum expression and ubiquity
- normalize and scale expression by any of several methods packaged in SingleCellExperiment
## Run clustering on a single object
By default clustering will be run at ten different resolutions between 0.2 and 2.0. Any resolution can be specified by providing the resolution argument as a numeric vector.
```{r, cache = FALSE, eval = FALSE}
clustered_sce <- sce_clustering_workflow(chevreul_sce,
experiment_name = "sce_hu_trans",
organism = "human"
)
```
## Get a first look at a processed dataset using an interactive shiny app
```{r, eval = FALSE}
minimalChevreulApp(chevreul_sce)
```
Owner
- Name: Cobrinik Laboratory at Children's Hospital Los Angeles
- Login: cobriniklab
- Kind: organization
- Location: Los Angeles, CA
- Website: https://www.chla.org/research/lab/cobrinik
- Repositories: 2
- Profile: https://github.com/cobriniklab
GitHub Events
Total
- Release event: 2
- Push event: 69
- Create event: 3
Last Year
- Release event: 2
- Push event: 69
- Create event: 3
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Last synced: 9 months ago
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