Below are the medians and 25%/75% quantiles of transcript abundances
of the main YRO cohorts in a series of
transcriptome time series of the YRO in different conditions and
strains.
The right plots show principal component analysis PCA of all genes
(colored by the main YRO cohorts) and the first two sample
eigenvectors that nicely form a circular pattern that
reproduces the sampling time. This property of PCA on gene expression
data has been recognized by Alter, Brown, and Botstein (2000)
(cf. eigengenes) and e.g. used to interpret YRO data
by Li and Klevecz
(2006); and was recently adopted to assign positions within the
cell division cycle of single cell transcriptome data (Schwabe et al. 2020).
We can cluster the first 20 PCA components by k-means to show that each
data set shows the same information, i.e., the same temporal program is
observed in all experiments.
The same reconstruction of the sampling times can be achieved by
running PCA on only the means of YRO cohorts. We will use this property
for a scalable method to analyse single cell
transcriptome snapshot data from asynchronous cultures in different
growth conditions.
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