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Release Notes

v 1.0.0

  • First public release.

v 1.1.7

bulk module:

  • Added Deseq2, including pyDEseq functions: deseq2_normalize, estimateSizeFactors, estimateDispersions, Matrix_ID_mapping.
  • Included TCGA with TCGA.
  • Introduced Enrichment with functions geneset_enrichment, geneset_plot.

single module:

  • Integrated scdrug with functions autoResolution, writeGEP, Drug_Response.
  • Added cpdb with functions cpdb_network_cal, cpdb_plot_network, cpdb_plot_interaction, cpdb_interaction_filtered.
  • Included scgsea with functions geneset_aucell, pathway_aucell, pathway_aucell_enrichment, pathway_enrichment, pathway_enrichment_plot.

v 1.1.8

single module:

  • Addressed errors in cpdb, including import errors and color issues in cpdb_plot_network.
  • Introduced cpdb_submeans_exacted in cpdb for easy sub-network extraction.

v 1.1.9

bulk2single module:

  • Added the bulk2single module.
  • Fixed model load error from bulk2space.
  • Resolved early stop issues from bulk2space.
  • Included more user-friendly input methods and visualizations.
  • Added loss history visualization.

utils module:

  • Introduced pyomic_palette in the plot module.

v 1.1.10

  • Updated all code references.

single module:

  • Fixed non-valid parameters in single.mofa.mofa_run function.
  • Added layer raw count addition in single.scanpy_lazy function.
  • Introduced utils.plot_boxplot for plotting box plots with jittered points.
  • Added bulk.pyDEseq.plot_boxplot for plotting box plots with jittered points for specific genes.

v 1.2.0

bulk module:

  • Fixed non-valid cutoff parameter in bulk.geneset_enrichment.
  • Added modules: pyPPI, pyGSEA, pyWGCNA, pyTCGA, pyDEG.

bulk2single module:

  • Introduced bulk2single.save for manual model saving.

v 1.2.1-4

single module:

  • Added pySCSA module with functions: cell_anno, cell_anno_print, cell_auto_anno, get_model_tissue.
  • Implemented doublet cell filtering in single.scanpy_lazy.
  • Added single.scanpy_cellanno_from_dict for easier annotation.
  • Updated SCSA database from CellMarker2.0.
  • Fixed errors in SCSA database keys: Ensembl_HGNC and Ensembl_Mouse.

v 1.2.5

single module:

  • Added pyVIA module with functions: run, plot_piechart_graph, plot_stream, plot_trajectory_gams, plot_lineage_probability, plot_gene_trend, plot_gene_trend_heatmap, plot_clustergraph.
  • Fixed warning error in utils.pyomic_plot_set.
  • Updated requirements, including pybind11, hnswlib, termcolor, pygam, pillow, gdown.

v 1.2.6

single module:

  • Added pyVIA.get_piechart_dict and pyVIA.get_pseudotime.

v 1.2.7

bulk2single module:

  • Added Single2Spatial module with functions: load, save, train, spot_assess.
  • Fixed installation errors for packages in pip.

v 1.2.8

  • Fixed pip installation errors.

bulk2single module:

  • Replaced deep-forest in Single2Spatial with Neuron Network for classification tasks.
  • Accelerated the entire Single2Spatial inference process using GPU and batch-level estimation by modifying the predicted_size setting.

v 1.2.9

bulk module:

  • Fixed duplicates_index mapping in Matrix_ID_mapping.
  • Resolved hub genes plot issues in pyWGCNA.plot_sub_network.
  • Fixed backupgene in pyGSEA.geneset_enrichment to support rare species.
  • Added matrix plot module in pyWGCNA.plot_matrix.

single module:

  • Added rank_genes_groups check in pySCSA.

bulk2single module:

  • Fixed import error of deepforest.

v 1.2.10

  • Renamed the package to omicverse.

single module:

  • Fixed argument error in pySCSA.

bulk2single module:

  • Updated plot arguments in bulk2single.

v 1.2.11

bulk module:

  • Fixed wilcoxon method in pyDEG.deg_analysis.
  • Added parameter setting for treatment and control group names in pyDEG.plot_boxplot.
  • Fixed figure display issues in pyWGCNA.plot_matrix.
  • Fixed category correlation failed by one-hot in pyWGCNA.analysis_meta_correlation.
  • Fixed network display issues in pyWGCNA.plot_sub_network and updated utils.plot_network to avoid errors.

v 1.3.0

bulk module:

  • Added DEseq2 method to pyDEG.deg_analysis.
  • Introduced pyGSEA module in bulk.
  • Renamed raw pyGSEA to pyGSE in bulk.
  • Added get_gene_annotation in utils for gene name transformation.

v 1.3.1

single module:

  • Added get_celltype_marker method.

single module:

  • Added GLUE_pair, pyMOFA, pyMOFAART module.
  • Added tutorials for Multi omics analysis by MOFA and GLUE.
  • Updated tutorial for Multi omics analysis by MOFA.

v 1.4.0

bulk2single module:

  • Added BulkTrajBlend method.

single module:

  • Fixed errors in scnocd model.
  • Added save, load, and get_pair_dict in scnocd model.

utils module:

  • Added mde method.
  • Added gz format support for utils.read.

v 1.4.1

preprocess module:

  • Added pp (preprocess) module with qc (quantity control), hvg (high variable feature), pca.
  • Added data_files for cell cycle calculation from Cellula and pegasus.

v 1.4.3

preprocess module: - Fixed sparse preprocess error in pp. - Fixed trajectory import error in via. - Added gene correlation analysis of trajectory.

v 1.4.4

single module:

  • Added panglaodb database to pySCSA module.
  • Fixed errors in pySCSA.cell_auto_anno when some cell types are not found in clusters.
  • Fixed errors in pySCSA.cell_anno when rank_genes_groups are not consistent with clusters.
  • Added pySIMBA module in single for batch correction.

preprocess module:

  • Added store_layers and retrieve_layers in ov.utils.
  • Added plot_embedding_celltype and plot_cellproportion in ov.utils.

v 1.4.5

single module:

  • Added MetaTiME module to perform cell type annotation automatically in TME.

v 1.4.12

  • Updated conda install omicverse -c conda-forge.

single module:

  • Added pyTOSICA module to perform cell type migration from reference scRNA-seq in Transformer model.
  • Added atac_concat_get_index, atac_concat_inner, atac_concat_outer functions to merge/concatenate scATAC data.
  • Fixed MetaTime.predicted when Unknown cell type appears.

preprocess module:

  • Added plot_embedding in ov.utils to plot UMAP in a special color dictionary.

v 1.4.13

bulk module:

  • Added mad_filtered to filter robust genes when calculating the network in ov.bulk.pyWGCNA module.
  • Fixed string_interaction in ov.bulk.pyPPI for string-db updates.

preprocess module:

  • Changed mode argument of pp.preprocess to control preprocessing steps.
  • Added ov.utils.embedding, ov.utils.neighbors, and ov.utils.stacking_vol.

v 1.4.14

preprocess module:

  • Added batch_key in pp.preprocess and pp.qc.

utils module:

  • Added plot_ConvexHull to visualize the boundary of clusters.
  • Added weighted_knn_trainer and weighted_knn_transfer for multi-adata integration.

single module:

  • Fixed import errors in mofa.

v 1.4.17

bulk module:

  • Fixed compatibility issues with pydeseq2 version 0.4.0.
  • Added bulk.batch_correction for multi-bulk RNA-seq/microarray samples.

single module:

  • Added single.batch_correction for multi-single cell datasets.

preprocess module:

  • Added parameter layers_add in pp.scale.

v 1.5.0

single module:

  • Added cellfategenie to calculate timing-associated genes/genesets.
  • Fixed the name error in atac_concat_outer.
  • Added more kwargs for batch_correction.

utils module:

  • Added plot_heatmap to visualize the heatmap of pseudotime.
  • Fixed embedding when the version of mpl is larger than 3.7.0.
  • Added geneset_wordcloud to visualize geneset heatmaps of pseudotime.

v 1.5.1

single module:

  • Added scLTNN to infer cell trajectory.

bulk2single module:

  • Updated cell fraction prediction with TAPE in bulk2single.
  • Fixed group and normalization issues in bulk2single.

utils module:

  • Added Ro/e calculation (by: Haihao Zhang).
  • Added cal_paga and plot_paga to visualize the state transfer matrix.
  • Fixed the read function.

v 1.5.2

bulk2single Module:

  • Resolved a matrix error occurring when gene symbols are not unique.
  • Addressed the interpolation issue in BulkTrajBlend when target cells do not exist.
  • Corrected the generate function in BulkTrajBlend.
  • Rectified the argument for vae_configure in BulkTrajBlend when cell_target_num is set to None.
  • Introduced the parameter max_single_cells for input in BulkTrajBlend.
  • Defaulted to using scaden for deconvolution in Bulk RNA-seq.

single Module:

  • Fixed an error in pyVIA when the root is set to None.
  • Added the TrajInfer module for inferring cell trajectories.
  • Integrated Palantir and Diffusion_map into the TrajInfer module.
  • Corrected the parameter error in batch_correction.

utils Module:

  • Introduced plot_pca_variance_ratio for visualizing the ratio of PCA variance.
  • Added the cluster and filtered module for clustering the cells
  • Integrated MiRA to calculate the LDA topic

v 1.5.3

single Module:

  • Added scVI and MIRA to remove batch effect

space Module:

  • Added STAGATE to cluster and denoisy the spatial RNA-seq

pp Module:

  • Added doublets argument of ov.pp.qc to control doublets('Default'=True)

v 1.5.4

bulk Module:

  • Fixed an error in pyDEG.deg_analysis when n_cpus can not be set in pyDeseq2(v0.4.3)

single Module:

  • Fixed an argument error in single.batch_correction of combat

utils Module:

  • Added venn4 plot to visualize
  • Fixed the label visualization of plot_network
  • Added ondisk argument of LDA_topic

space Module:

  • Added Tangram to mapping the scRNA-seq to stRNA-seq

v 1.5.5

pp Module:

  • Added max_cells_ratio and max_genes_ratio to control the max threshold in qc of scRNA-seq

single Module:

  • Added SEACells model to calculate the metacells from scRNA-seq

space Module:

  • Added STAligner to integrate multi stRNA-seq

v 1.5.6

pp Module

  • Added mt_startswith argument to control the qc in mouse or other species.

utils Module

  • Added schist method to cluster the single cell RNA-seq

single Module

  • Fixed the import error of palantir in SEACells
  • Added CEFCON model to identify the driver regulators of cell fate decisions

bulk2single Module

  • Added use_rep and neighbor_rep argument to configure the nocd

space Module

  • Added SpaceFlow to identify the pseudo-spatial map

v 1.5.8

pp Module

  • Added score_genes_cell_cycle function to calculate the cell cycle

bulk Module

  • Fixed dds.plot_volcano text plot error when the version of adjustText larger than 0.9

single Module

  • Optimised MetaCell.load model loading logic
  • Fixed an error when loading the model usng MetaCell.load
  • Added tutorials of Metacells

pl Module

Add pl as a unified drawing prefix for the next release, to replace the drawing functionality in the original utils, while retaining the drawing in the original utils.

  • Added embedding to plot the embedding of scRNA-seq using ov.pl.embedding
  • Added optim_palette to provide a spatially constrained approach that generates discriminate color assignments for visualizing single-cell spatial data in various scenarios
  • Added cellproportion to plot the proportion of stack bar of scRNA-seq
  • Added embedding_celltype to plot the figures both celltype proportion and embedding
  • Added ConvexHull to plot the ConvexHull around the target cells
  • Added embedding_adjust to adjust the text of celltype legend in embedding
  • Added embedding_density to plot the category density in the cells
  • Added bardotplot to plot the bardotplot between different groups.
  • Added add_palue to plot the p-threshold between different groups.
  • Added embedding_multi to support the mudata object
  • Added purple_color to visualize the purple palette.
  • Added venn to plot the venn from set 2 to set 4
  • Added boxplot to visualize the boxdotplot
  • Added volcano to visualzize the result of differential expressed genes

v 1.5.9

single Module

  • Added slingshot in single.TrajInfer
  • Fixed some error of scLTNN
  • Added GPU mode to preprocess the data
  • Added cNMF to calculate the nmf

space Module

  • Added Spatrio to mapping the scRNA-seq to stRNA-seq