Hi,
I've read the tutorial documents and re run it at local, but I didn't see any information about how to create the classifier. If the script about producing PBMC classifier is available, could you update it to repository? Thank you!

It would be greater than great if Moana could be installed via anaconda/miniconda. Admittedly, I have no idea how much work this involves.

Hi,

It will be great if you could port Moana to R or write a wrapper for R. Most of us use Seurat and Monocle, and it will be much easier to use Moana if it were integrated in the R environment.

Thanks.

Hi,

I followed the installation guidance and tutorial and was trying to read the example .mtx file, which throws the following error. Any idea? And my real data come from 10x cellranger 3.0, is there a function to read the new format? Thanks.

read expression matrix

matrix = ExpMatrix.read_sparse(expression_file)

ValueError Traceback (most recent call last)
in
5
6 # read expression matrix
----> 7 matrix = ExpMatrix.read_sparse(expression_file)
8 # # perform smoothing
9 # k = 128

~/anaconda3/envs/moana/lib/python3.7/site-packages/moana/core/exp_matrix.py in read_sparse(cls, file_path)
380 genes = next(fh)[1:-1].split('\t')
381 next(fh)
--> 382 m, n, nnz = [int(s) for s in next(fh)[:-1].split(' ')]
383
384 t = pd.read_csv(file_path, sep=' ', skiprows=5, header=None,

~/anaconda3/envs/moana/lib/python3.7/site-packages/moana/core/exp_matrix.py in (.0)
380 genes = next(fh)[1:-1].split('\t')
381 next(fh)
--> 382 m, n, nnz = [int(s) for s in next(fh)[:-1].split(' ')]
383
384 t = pd.read_csv(file_path, sep=' ', skiprows=5, header=None,

ValueError: invalid literal for int() with base 10: ''