Table 1.

Results from standard PCA, EESPC, EESPCA.cv, SPC, SPC.1se, TPower and rifle analysis of the PBMC scRNA-seq data following the procedure detailed in Section 2.4. The table lists the number of the 1,000 genes in the input data matrix that were assigned positive or negative loadings. Since standard PCA produces non-zero loadings for all genes, the magnitude of the difference between the PCA counts and the counts for the other methods reflects the relative sparsity of the solutions. The “sig. GO” columns capture the number of Gene Ontology Biological Process terms that were significantly enriched among the genes with either positive or negative loadings at an FDR of ≤ 0.1. The relative reconstruction error captures average out-of-sample reconstruction error measured over 10 random splits of the data relative to the error for standard PCA (standard deviation is included in parentheses). For each split, PCs were estimated using each method on half of the data and the squared Frobenius norm of the residual matrix for the first two PCs was computed for the other half of the data.

	PC 1				PC 2				Relative
	Positive		Negative		Positive		Negative		reconstruction
	genes	sig. GO	genes	sig. GO	genes	sig. GO	genes	sig. GO	error
PCA	558	44	442	0	316	0	684	0	1 (0)
EESPCA	134	104	12	0	35	38	83	3	1.004 (0.0005)
EESPCA.cv	166	89	22	0	41	33	129	14	1.003 (0.0004)
SPC	535	37	418	0	316	0	684	0	0.996 (0.003)
SPC.1se	193	84	36	0	91	21	394	1	1.003 (0.0002)
TPower	485	38	357	0	226	3	616	0	1.0002 (0.0003)
rifle	485	38	357	0	268	2	574	2	1.002 (0.002)