Update README.md

README.md

@@ -52,7 +52,7 @@ Steps 1-8 are performed using [scrnabox.slurm](https://github.com/neurobioinfo/s
 - **Step 2.1: Ambient RNA removal** - The ambient RNA rate is estimated and the gene expression profiles are corrected for RNA contamination (optional) using SoupX (Young et al. 2020).<br />
 - **Step 2.2: Create Seurat object** - CellRanger- or SoupX-generated feature-barcode expression matrices are transformed into Seurat objects. Genes expressed in less than a minimum number of cells and cells expressing less than a minimum number of genes can be filtered.<br />
 - **Step 3: Quality control and filtering** - Low quality cells are filtered based on the user-defined thresholds for the number of genes detected per cell,	number of unique transcripts detected per cell, percentage of mitochondrial-encoded transcripts, and percentage of ribosomal-encoded transcripts. In addition, mitochondrial- and ribosomal-encoded genes can be filtered out.<br />
-- **Step 4: Doublet removal** - Doublets are identified and removed from downstream analysis (optional) using the DoubletFinder tool (McGinnis et al. 2019).<br />
+- **Step 4: Demultiplexing and Doublet removal** -  Seurat’s implementation (_MULTIseqDemux_) of the tag assignment algorithm outlined in Multi-seq to demultiplex pooled samples and identify doublets according to the expression matrices of the sample-specific barcodes (McGinnis et al 2019).<br />
 - **Step 5: Integration and linear dimensional reduction** - Individual Seurat objects are integrated to enable the joint analysis across sequencing runs using Seurat's integration algorithm (Stuart et al. 2019); if experiments are limited to a single sequencing run, the integration Step can be bypassed. Linear dimensional reduction is then performed on the resulting Seurat object to inform the optimal parameters for clustering in Step 6.<br />
 - **Step 6: Clustering** - Clustering is performed to define groups of cells with similar expression profiles using the graph-based clustering approach implemented in the Seurat framework (Macosko et al. 2015).<br />
 - **Step 7: Cluster annotation** - Cell populations, or clusters, with similar expression profiles are annotated to define cell types by three distinct methods:<br />