bbknn | intuitive batch effect removal tool that can be | Genomics library

bbknn is a Python library typically used in Artificial Intelligence, Genomics applications. bbknn has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install bbknn' or download it from GitHub, PyPI.

BBKNN is a fast and intuitive batch effect removal tool that can be directly used in the scanpy workflow. It serves as an alternative to scanpy.pp.neighbors(), with both functions creating a neighbour graph for subsequent use in clustering, pseudotime and UMAP visualisation. The standard approach begins by identifying the k nearest neighbours for each individual cell across the entire data structure, with the candidates being subsequently transformed to exponentially related connectivities before serving as the basis for further analyses. If technical artifacts (be they because of differing data acquisition technologies, protocol alterations or even particularly severe operator effects) are present in the data, they will make it challenging to link corresponding cell types across different batches. As such, BBKNN actively combats this effect by taking each cell and identifying a (smaller) k nearest neighbours in each batch separately, rather than the dataset as a whole. These nearest neighbours for each batch are then merged into a final neighbour list for the cell. This helps create connections between analogous cells in different batches without altering the counts or PCA space.