From Array Suite Wiki
1. Preprocess of SingleCell RNA-Seq Data - Compared to the raw data QC like adapter stripping and quality trimming for normal fastq file, for Single-cell fastq file, it's important to extract the barcodes and UMI information before doing the alignment. The preprocess module for Single-cell RNASeq can be accessed from NGS | Single Cell RNA-Seq | Single Cell Preprocessing)
2. Demultiplex - User can specify whether to do Demultiplex in the preprocess of fastq files (in the options, set /Demultiplex=TRUE(or FALSE)). If user set it to be TRUE, the fastq files will be separated into single fastq file for each barcode. If user set it to FALSE, the fastq files will not be separated in the preprocess step and the demultiplex will happen in the process of quantification, in which way, the data (fastq file and BAM file) will be more concise as all barcodes information are compacted in single fastq/bam file.
3. Alignment of SingleCell RNA-Seq Data - Alignment of your SingleCell RNA-Seq to a reference is similar to the normal RNASeq alignment and will use the same module, while in ArrayStuio GUI, there are different menu. If your data has not been aligned, you can do the alignment through NGS | Single Cell RNA-Seq | Barcoded Alignment. During this alignment process, ArrayStudio will search for the corresponding tag file in the same directory of fastq file, and store the tag information into the BAM file. The BAM file containing the mapped reads information and also the information for barcode/UMI and can be used for the following analysis.
4. Quantification of SingleCell RNA-Seq - After alignment, the user can quantify the aligned BAM files. This includes calculation of RPKM (for visually comparing across samples or running some downstream analysis), or the calculation of count data (to be used by DESeq for detection of differential expression).