1 About

1.1 Introduction

The SingleCellMQC pipeline is developed in R and accepts input files from scRNA-seq, surface protein seqencing, scTCR-seq, and scBCR-seq to perform QC analysis. The pipeline utilizes the Seurat and BPCells objects to store and analyze large data. The pipeline consists of four major QC modules: (i) sample QC, (ii) cell QC, (iii) feature QC, and (iv) batch QC. Each module encompasses a range of functions, including QC metrics assessment, outlier sample detection, abnormal cell identification, background noise detection, batch effect evaluation, etc. Data visualization for each module encompasses a variety of elements, including static graphs, interactive graphs, and interactive tables. In particular, each module supports the generation of HTML reports for multi-omics quality control (QC) based on R Markdown, which contains QC results and potential warnings.

1.2 Installation

Before installation, we recommend installing these dependencies first:

Seurat (single-cell analysis toolkit)
BPCells (memory-efficient single-cell data processing)

You can install the development version of SingleCellMQC from GitHub with:

if (!requireNamespace("devtools", quietly = TRUE)) {
  install.packages("devtools")  
}
devtools::install_github('WenZhong-Lab/SingleCellMQC') 
library(SingleCellMQC)

1.3 Bugs

If you encounter any issues or have questions, please open an issue on GitHub. We’ll be happy to assist!