Clustering in single-cell RNA-seq — the standard pipeline.

hard

Answer

$(1) QC + normalize (log-CPM, SCTransform).$
$(2) HVG selection.$
$(3) PCA to 50 dim.$
$(4) Batch correction (Harmony, scVI).$
$(5) k-NN graph in PCA space.$
$(6) Leiden community detection.$
$(7) UMAP for visualization.$
$(8) Marker gene analysis per cluster to identify cell types.$
$Modern: scVI / scANVI for VAE-based normalization + integration; totalVI for multimodal (CITE-seq).$

Check yourself — multiple choice

Just k-means
QC + normalize + HVG + PCA + batch correct (Harmony/scVI) + k-NN graph + Leiden + UMAP viz + marker analysis; standard scanpy/Seurat pipeline
Random
Not real

scRNA-seq: normalize + PCA + batch correct + Leiden + UMAP + markers.

#applications#clustering

214 interview questions in this topic.