# sell

**Repository Path**: rainoffallingstar/sell

## Basic Information

- **Project Name**: sell
- **Description**: An R package in development for Single cELL analysis by using R6 object.
- **Primary Language**: R
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2023-12-20
- **Last Updated**: 2024-06-07

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README


<!-- README.md is generated from README.Rmd. Please edit that file -->

# sell

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<img src="https://github.com/rainoffallingstar/sell/blob/master/dev/sell.png" height="200" align="right"/>
The goal of sell is to build a R6-based package for singlecell analysis.
Now warped with Seurat V4/V5.

## Installation

You can install the development version of sell:

``` r
# FILL THIS IN! HOW CAN PEOPLE INSTALL YOUR DEV PACKAGE?
pak::pak("rainoffallingstar/sell")
```

## Example

This is a basic example which shows you how to solve a common problem:

``` r
library(sell)
## basic example code
## check seurat api
seurat_api_detect()

## encode your array and pdata into seurat object and take computation
seurat_object <- seurat_encoder(newdata[["arraydata"]],newdata[["pdata"]],min.cells = 0,
                           min.features = 0,reduction_dims = 1:5)
## extract datas from seurat container

sell_list <- seurat_decoder(seurat_object)

## creat a R6 object for single cell: BagEnd
## In a hole in the ground there lived a lot of cells,lol

sellobject <- BagEndClass$new(arraydata = arraydata,pdata = pdata)

## select interested samples and gene and transform into a long table for further works
sell_melt_df <- intersect_array_pdata(arraydata,pdata) %>% 
  sell_melt()
```