双虚拟敲除 CellOracle + scTenifoldKnk 全流程复现（二）
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TL;DR - Part two of a WeChat tutorial series reproducing a 2026 Cell Prolif paper that used dual virtual knockout (CellOracle + scTenifoldKnk) to identify STAT3 as a dentinogenesis regulator; this installment covers the single-cell QC and cell-type annotation steps on GSE146123 in R/Seurat.
- QC thresholds were chosen after an AI-assisted literature scan of dental pulp/odontogenic scRNA-seq papers (MT% cutoffs ranging 5%–40% across Pang 2023, Yang 2024, Zhang 2026, Liu 2026); the author settled on nFeature_RNA 200–6000, nCount_RNA 3–30000, percent_mito <10%, percent_hb <1%.
- Standard Seurat pipeline: LogNormalize (scale factor 1e4), 2000 variable features, ScaleData, PCA, then Harmony integration on
orig.identto correct sample batch effects, with UMAP/neighbors on dims 1:20. - Clustering resolution was swept over 0.05–1 and inspected with
clustree; resolution 0.5 was used for the working annotation. - Annotation targets the original paper's 9 major populations (endothelial 21.2%, mesenchymal 20.7%, perivascular 16.9%, glial, peri-odontoblastic layer, pulp, preodontoblasts, epithelial, immune), with marker-based distinctions noted (mesenchymal: COL1A1/DCN/LUM vs. pulp: VIM/BGN/POSTN).
- Note: content is truncated mid-annotation, and the actual CellOracle/scTenifoldKnk perturbation steps are deferred to later installments.
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双虚拟敲除 CellOracle + scTenifoldKnk 全流程复现（二）
Public signals
N/A
TL;DR - Part two of a WeChat tutorial series reproducing a 2026 Cell Prolif paper that used dual virtual knockout (CellOracle + scTenifoldKnk) to identify STAT3 as a dentinogenesis regulator; this installment covers the single-cell QC and cell-type annotation steps on GSE146123 in R/Seurat.
- QC thresholds were chosen after an AI-assisted literature scan of dental pulp/odontogenic scRNA-seq papers (MT% cutoffs ranging 5%–40% across Pang 2023, Yang 2024, Zhang 2026, Liu 2026); the author settled on nFeature_RNA 200–6000, nCount_RNA 3–30000, percent_mito <10%, percent_hb <1%.
- Standard Seurat pipeline: LogNormalize (scale factor 1e4), 2000 variable features, ScaleData, PCA, then Harmony integration on
orig.identto correct sample batch effects, with UMAP/neighbors on dims 1:20. - Clustering resolution was swept over 0.05–1 and inspected with
clustree; resolution 0.5 was used for the working annotation. - Annotation targets the original paper's 9 major populations (endothelial 21.2%, mesenchymal 20.7%, perivascular 16.9%, glial, peri-odontoblastic layer, pulp, preodontoblasts, epithelial, immune), with marker-based distinctions noted (mesenchymal: COL1A1/DCN/LUM vs. pulp: VIM/BGN/POSTN).
- Note: content is truncated mid-annotation, and the actual CellOracle/scTenifoldKnk perturbation steps are deferred to later installments.