Train a PLIER model on a dataset that is aggregated by species

Related: https://github.com/AlexsLemonade/refinebio-examples/issues/24

If we pick a large (enough) dataset that we aggregate by species for our batch correction example, we can then use it as training data for PLIER. Specifically, @cansav09 have talked about obtaining many datasets from a particular cell line (e.g., MCF-7, HEK293) for the batch correction example. We can then potentially train a PLIER model on the data with and without batch correction and compare. We'll have to be a bit careful about how we frame the comparison, though, as users may be linked from the docs to this example. We'll need to include sufficient context. cc @dvenprasad

Start with related issue #24 and the proposed species-aggregated dataset for the batch-correction example. Determine how PLIER training should use data with and without batch correction, and define the context users need before being linked from the documentation. Done means the dataset, training and comparison workflow, and explanatory example are specified and completed.

Written by the indexing model from the issue text.