In this video, I will present you
the shinny application scMonitor, which is
oriented to easily explore
a previously processed seurat object.
Firstly, you should select the file
containing the seurat object.
For now, the file format must be RDS.
Depending on the object size and
computer potency the loading
will take more or less time.
UMAP distribution that generates
is the same that shows as default,
usually clusters identified by seurat itself.
We can group colors by any
other variable that we have included in the
metadata from the object specifying it in "GroupBy".
Tipically, the sample origin or
a manual annotation
from the cell type.
Distribution can also be divided by
another variable selecting in "FacetBy".
In this case, we are looking at
the distribution of cell type
by the sample origin.
Another available visualization is to show expression
for a group of genes separated by a white space
over UMAP distribution.
With the "Height" bar we can adjust
the size in order to feel comfortable.
Finally, we can create signatures in order to visualize
their score from cells.
One must indicate the signature name and
on the box below specify the genes
that are included. Once added, you can
specify its name in the
signatures box.