Skip to main content
Fig. 2 | Genome Biology

Fig. 2

From: SCoPE-MS: mass spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation

Fig. 2

Identifying protein covariation across differentiating ES cells. a Clustergrams of pairwise protein-protein correlations in cells differentiating for 3, 5, and 8 days after LIF withdrawal. The correlation vectors were hierarchically clustered based on the cosine of the angles between them. All single-cell sets used the same carrier channel which was comprised of cells mixed from different time points. b The similarity between the correlation matrices shown in panel a is quantified by the distribution of correlations between corresponding correlation vectors, as we previously described [42]. Medians are marked with green squares and means with red pluses. c All pairwise Pearson correlations between ribosomal proteins (RPs) were computed by averaging across cells. The correlation matrix was clustered, using the cosine between the correlation vectors as a similar measure. d To evaluate the similarity in the relative levels of functionally related proteins, we computed the Pearson correlations within sets of functionally related proteins as defined by the gene ontology (GO). These sets included protein complexes, lineage-specific proteins, and proteins functioning in cell growth and division. The distribution of correlations for all quantified proteins is also displayed and used as a null distribution. To remove a positive bias from the null distribution, we subtracted the contribution of the first pair of singular vectors from the matrix of protein levels since this pair often concentrates global effects, which include batch effects and other system-wide trends [42, 54]. The difference between the distributions of correlations for the protein clusters and the null distribution is present in the raw data before this normalization

Back to article page