anndata - Annotated Data¶
pip install anndata or
conda install anndata -c bioconda.
Report issues and see the code on GitHub.
anndata is for simple (functional) high-level APIs for data analysis pipelines. In this context, it provides an efficient, scalable way of keeping track of data together with learned annotations and reduces the code overhead typically encountered when using a mostly object-oriented library such as scikit-learn.
See all releases here. The following lists selected improvements.
May 1, 2018: version 0.6
- compatibility with Seurat converter
- tremendous speedup for
April 17, 2018: versions 0.5.9 - 0.5.10
- bug fix for deep copy of unstructured annotation after slicing
March 16, 2018: versions 0.5.1 - 0.5.8
- bug fix for reading HDF5 stored single-category annotations
- ‘outer join’ concatenation: adds zeros for concatenation of sparse data and nans for dense data
- better memory efficiency in loom exports
- consistency and documentation updates
- prettified print output
There was a bug in
concatenate() in versions 0.5.2,
0.5.3 and 0.5.4: variable names were not assigned correctly. Was fixed in
February 9, 2018: version 0.5
- inform about duplicates in
var_namesand resolve them using
- automatically remove unused categories after slicing
- read/write .loom files using loompy 2
- some IDE-backed improvements
December 29, 2017: version 0.4.2
December 23, 2017: version 0.4
- towards a common file format for exchanging
AnnDatawith packages such as Seurat and SCDE by reading and writing .loom files
AnnDataprovides scalability beyond dataset sizes that fit into memory: see this blog post
rawattribute that simplifies storing the data matrix when you consider it “raw”: see the clustering tutorial