A low rank complement method based on scRNA-seq data
Project description
For the data matrix of scRNA-seq, each cell is treated as a sample, and each row (column) indicates the expression of different genes in this cell is affected by noise.In summary, we have developed a low rank constraint matrix completion method based on truncated kernel norm.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
zimpute-1.7.tar.gz
(9.6 kB
view hashes)
Built Distribution
zimpute-1.7-py3.7.egg
(18.0 kB
view hashes)