Extended Data Fig. 5: Multiple computational approaches for trajectory inference of PbTII scRNA-seq data. | Nature Immunology

Extended Data Fig. 5: Multiple computational approaches for trajectory inference of PbTII scRNA-seq data.

From: Transcriptome dynamics of CD4+ T cells during malaria maps gradual transit from effector to memory

Extended Data Fig. 5: Multiple computational approaches for trajectory inference of PbTII scRNA-seq data.

a, (left) UMAP representation of batch-corrected Smart-seq2 PbTII dataset superimposed with trajectory inferences calculated using Slingshot. (right) Visualising Cxcr6 and Cxcr5 expression on UMAP representations as described previously. b, Grid-view of RNA velocities for each cell from the Smart-seq2 PbTII dataset (only D4-D28 p.i.) visualised on 2D bGPLVM representations. c, (left) Integration of the three PbTII datasets (Smart-seq2(96/ 384) and SMARTer) using scVI represented on a UMAP plot. (right) Visualising Cxcr6 and Cxcr5 on a UMAP representation of the scVI-integrated dataset.

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