New in 0.12.0 (2021-07-15)#
This release adds features for tighter integration with Pyro for model development, fixes for SOLO
, and other enhancements. Users of SOLO
are strongly encouraged to upgrade as previous bugs will affect performance.
Enchancements#
Add
scvi.model.base.PyroSampleMixin
for easier posterior sampling with Pyro (#1059).Add
scvi.model.base.PyroSviTrainMixin
for automated training of Pyro models (#1059).Ability to pass kwargs to
Classifier
when usingSOLO
(#1078).Ability to get doublet predictions for simulated doublets in
SOLO
(#1076).Add “comparison” column to differential expression results (#1074).
Clarify
CellAssign
size factor usage. See class docstring.
Changes#
Update minimum Python version to
3.7.2
(#1082).Slight interface changes to
PyroTrainingPlan
."elbo_train"
and"elbo_test"
are now the average over minibatches as ELBO should be on scale of full data andoptim_kwargs
can be set on initialization of training plan (#1059, #1101).Use pandas read pickle function for pbmc dataset metadata loading (#1099).
Adds
n_samples_overall
parameter to functions for denoised expression/accesibility/etc. This is used in during differential expression (#1090).Ignore configure optimizers warning when training Pyro-based models (#1064).
Bug fixes#
Fix scale of library size for simulated doublets and expression in
SOLO
when using observed library size to train originalSCVI
model (#1078, #1085). Currently, library sizes in this case are not appropriately put on the log scale.Fix issue where anndata setup with a layer led to errors in
SOLO
(#1098).Fix
adata
parameter ofscvi.external.SOLO.from_scvi_model()
, which previously did nothing (#1078).Fix default
max_epochs
ofSCANVI
when initializing using pre-trained model ofSCVI
(#1079).Fix bug in
predict()
function ofSCANVI
, which only occurred for soft predictions (#1100).
Breaking changes#
None!