README.md

In Meiomap/SureTypeSCR: Library for (single-cell) SNP array processing

SureTypeSCR

Introduction

SureTypeSCR is an R package for QC and rapid genotyping of single cell SNP array data. It encapsulates previously developed library SureTypeSC (paper). The core consists of a two layered machine learning method that assigns a quality score to each SNP in an array. On top of that, SureTypeSCR implements various QC strategies to examine the data using packages from the tidyverse collection.

Prerequisites

The following is needed prior to the installation: R (>=4.0). Python 3 (>= 3.6) * devtools (R)

Installation

It is preferred to install the package using devtools.

install.packages('devtools')
library('devtools')
##install  SureTypeSCR  from  github
devtools::install_github("Meiomap/SureTypeSCR")

Alternatively, user can download current release and then install the package using following command

R CMD INSTALL SureTypeSCR_0.99.0.tar.gz

Package initialization and sample data loading

When loaded for the first time, SureTypeSCR will create a python virtual environment and install all required python libraries via python package installer (pip). A sample data and metadata deployed with the package can be used for testing whether the pakcage was installed and loaded correctly.

library(SureTypeSCR)

setwd(system.file(package='SureTypeSCR'))
samplesheet=system.file('files/GSE19247_example.csv',package='SureTypeSCR')
manifest=system.file('files/HumanCytoSNP-12v2_H.bpm',package='SureTypeSCR')
cluster=system.file('files/HumanCytoSNP-12v2_H.egt',package='SureTypeSCR')

#Load data
df=scbasic(manifest,cluster,samplesheet)

Documentation

See tutorial and reference manual for complete documentation. An inline help for a particular function can be invoked withing the code by typing ?function_name.

Further information

In case you are seeking for additional information or have problems installing or using the software, please write to ivogel[at]sund.ku.dk or report an issue in the Issues tracker.

Meiomap/SureTypeSCR documentation built on Dec. 17, 2021, 3:22 a.m.