Update website/docs/Pipelines/Optimus_Pipeline/optimus.methods.md

Co-authored-by: Elizabeth Kiernan <[email protected]>

website/docs/Pipelines/Optimus_Pipeline/optimus.methods.md

@@ -9,7 +9,7 @@ Below we provide an example methods section for a publication, separated into si
 # Methods
 
 ## Single-cell (sc_rna mode)
-Data preprocessing and count matrix construction were performed using the Optimus v7.8.1 pipeline (RRID:SCR_018908). Briefly, FASTQ files were partitioned by barcodes using sctools v0.3.13. The files were then trimmed, aligned, UMI-corrected against the 10x Genomics barcodes whitelist, and converted to a raw count matrix using STAR v2.7.9a. CB correction was performed using the `--soloCBmatchWLtype 1MM_multi_Nbase_pseudocounts` parameter which allowed for multiple matches in the whitelist with 1 mismatched base, used posterior probability calculation to choose one of the matches, added pseudocounts of 1 to all whitelist barcodes, and allowed multi-matching of CBs with N-bases to the whitelist.
+Data preprocessing and count matrix construction were performed using the Optimus v7.8.1 pipeline (RRID:SCR_018908). Briefly, FASTQ files were partitioned by barcodes using fastqprocess. The files were then trimmed, aligned, UMI-corrected against the 10x Genomics barcodes whitelist, and converted to a raw count matrix using STARsolo v2.7.11a. CB correction was performed using the `--soloCBmatchWLtype 1MM_multi` parameter.
 
 Reads were trimmed using the solo parameter `--clipAdapterType CellRanger4` and `--outFilterScoreMin 30` which matches read trimming performed by CellRanger4. Reads were then aligned to GENCODE mouse (M21) or human (V27) references in unstranded mode. Genes were annotated using the STAR "Gene" COUNTING_MODE and UMIs were corrected with the `--soloUMIdedup 1MM_CR` parameter, which uses a directional correction method. The resulting BAM was then used for cell and gene metric correction using the sctools v0.3.13 TagSortBam tool. The STAR TSV outputs for gene counts, features, and barcodes were converted to numpy arrays for downstream empty droplet detection using DropletUtils v1.2.1 emptyDrops with the parameters `--fdr-cutoff 0.01 --emptydrops-niters 10000 --min-molecules 100 --emptydrops-lower 100.`