SDePER v1.6.2

Bug Fixes:

• Upgrade certain dependencies to ensure successful installation via both PyPI and Conda.

SDePER v1.6.1

Bug Fixes:

• Changed the dependency to the headless version of OpenCV to avoid installation issues and since no GUI functionality is required.

SDePER v1.6.0

Updates:

• The imputation module has been completely rewritten, significantly improving contour finding and grid generation for enhanced performance and accuracy (#1).

SDePER v1.5.0

Updates:

• The optimization of cell type proportion $\theta$ is skipped if the initial value of $\theta$ indicates the presence of only one cell type in the spot.

• When predicting cell type proportions utilizing the CVAE latent space, the values of the CVAE latent space are now directly used instead of PCA embeddings for proportion transferring.

• The default number of hidden layers has been changed from 2 to 1.

SDePER v1.4.0

Updates:

• Added single cell augmentation feature for scRNA-seq reference data.

• Implemented failure steps for handling irregular $\theta$ values after optimization.

• Added support for transferring cell type proportions based on PCA or UMAP embeddings of latent space, or directly on the original latent space in cell type proportion prediction using CVAE.

• Introduced caching in GLRM to accelerate computations by storing calculated likelihood values, reducing duplicate calculations. Note: This feature is disabled by default due to potential optimization failures caused by unknown reasons (#5).

Bug Fixes:

• Resolved issue with spot name inconsistencies when spots are filtered out if cell type proportions predicted by CVAE were used for $\theta$ initialization in GLRM modeling.

• Fixed bug causing errors when plotting CVAE loss during training in the absence of validation data.

SDePER v1.3.1

Updates:

• Added a step to remove mitochondrial genes during preprocessing.

• Introduced a PCA plot for visualizing the latent space and added density estimation based on PCA in diagnostic figures.

SDePER v1.3.0

Updates:

• Introduced prediction of cell type proportions utilizing the CVAE latent space. Currently, the proportions are transferred from the scRNA-seq condition to the spatial condition in latent space. Then the predicted cell type proportions are used as initial value of $\theta$ for GLRM modeling (#13).

• Reused $\theta$ and $e^{\alpha}$ estimations from stage 1 of GLRM modeling for initializing stage 2 (#12).

• Increased the weight of spatial spots and scRNA-seq cells in CVAE training against generated pseudo-spots.

• Added support for retaining only highly variable genes in the spatial data. By default all genes are retained.

• SDePER options are written to a text file within the diagnosis folder, and only DE genes are retained in the CVAE-transformed data during saving if command-line option --redo_de is true.

• Decreased the default number of command-line option --n_pseudo_spot to 100,000.

Bug Fixes:

• Resolved a bug where errors occurred during diagnostic UMAP drawing if only cell type markers were provided, and no scRNA-seq cells were available.

SDePER v1.2.1

Updates:

• Implemented a GitHub Action triggered by new release publications to test the package installation (#10).

• Added a diagnostic UMAP plot of raw data before platform effect removal using CVAE. Also included new diagnostic plots depicting CVAE training loss.

• Changed the default value of the --n_marker_per_cmp command-line option to 20.

• Added three command-line options: --use_batch_norm, --use_spatial_pseudo and --cvae_train_epoch.

SDePER v1.2.0

Updates:

• Revised the cvae module, implementing several updates including (#4):

  • Integration of Batch Normalization into the CVAE training process.

  • Inclusion of a logarithmic transformation in the preprocessing of gene expression data for CVAE input.

  • Generation of “pseudo-spots” under spatial conditions through the random combination of spatial spots.

  • Addition of two command-line options: --n_pseudo_spot and --num_hidden_layer. Also adjusted the default value of --cvae_init_lr.

• Relocated all code related to generating diagnostic figures to a new module, diagnosis_plots. Additionally organized the output figures into a folder named diagnosis within the output path (#6).

SDePER v1.1.0

Updates:

• Improved differential analysis strategy for maker gene identification. Added 8 new related options and modified the default value of 2 options (#3).

• Updated help messages (#7).

• Add support for installation via Conda (#2, #8).

• Add source code and relevant documentation into the package documentation (#9).