Fig. 4: Estimate biological features of a new dataset using the signatures learned from public databases. | Nature Communications

Fig. 4: Estimate biological features of a new dataset using the signatures learned from public databases.

From: GenomicSuperSignature facilitates interpretation of RNA-seq experiments through robust, efficient comparison to public databases

Fig. 4

RAVs encompass biological signals applicable across different platforms and independent datasets. We demonstrate this transfer learning capacity of RAVs by identifying the neutrophil-associated RAV from systemic lupus erythematosus whole blood (SLE-WB) data and using the same RAV to analyze nasal brushing (NARES) dataset. a Neutrophil counts of 853 samples from the SLE-WB dataset were plotted against RAV1551-assigned sample scores. b Neutrophil count estimates by MCPcounter were plotted against sample scores assigned by RAV1551. c Neutrophil count of 76 NARES samples were estimated by MCPcounter and plotted against RAV1551-assigned sample scores. The shaded area is the 95% confidence interval for predictions from a linear model.

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