Using Seurat to analyze single-cell RT-qPCR datasets (Biomark, Fluidigm)

[fxmauvais]

Hello, I am analyzing an old dataset of single-cell RT-qPCR of flow cytometry sorted humaj CD8+ T lymphocytes from 4 groups of individuals (total aroung 40 individuals/runs).

Runs were performed using fluidigm technology C1 autoprep + Biomark (up to 96 cells / chip with 94 genes including two housekeeping genes). Each chip = one individual. I have done the preprocessing steps, e.g. conversion of ct values, normalization of gene expression to the geometric mean of the expression of the two housekeeping genes.

I have looked for tools to perform batch correction and subsequent data analysis (e.g. clustering, differential expression etc), but I have not found such, probably because they were mainly developed for scRNA-seq analysis which has replaced scRT-qPCR.

I was wondering whether I may use Seurat to do the analysis of my dataset (multiple runs of single-cell RT-qPCR) and if so whether the main functions/steps of Seurat analytic pipeline may be applied (or what should I change). Also planning to apply Harmony to correct for batch-effect.

Thank you for reading and advices and best wishes for 2026