Reverse Dependencies of session-info

The following projects have a declared dependency on session-info:

• balance — balance is a Python package offering a simple workflow and methods for dealing with biased data samples when looking to infer from them to some target population of interest.
• besca — Collection of BEDA internal python functions for analysing single cell RNAseq data.
• biolord — A deep generative framework for disentangling known and unknown attributes in single-cell data.
• bolero — sequence
• bolero-process — Data preprocessing for bolero package
• cellcharter — A Python package for the identification, characterization and comparison of spatial clusters from spatial -omics data.
• celldino — Cellular decomposition of intrinsic and niche-induced omic effects
• drvi-py — Disentangled Generative Representation of Single Cell Omics
• dummy-anndata — Allows generating dummy anndata objects, useful for testing.
• dynamo-release — Mapping Vector Field of Single Cells
• ehrapy — Electronic Health Record Analysis with Python.
• ehrdata — A Python package for EHR data
• eschr — A hyperparameter-randomized ensemble approach for robust clustering across diverse datasets
• feature-clock — Feature Clock, provides visualizations that eliminate the need for multiple plots to inspect the influence of original variables in the latent space. Feature Clock enhances the explainability and compactness of visualizations of embedded data.
• formulaic-contrasts — Build contrasts for models defined with formulaic
• fosfairy — TFs, IEGs and more!
• gefslim — A minimal reader for .gef files
• genomic-features — Genomic annotations using BioConductor resources in Python.
• geome — Geometric Learning for Genome Data
• histgram — Long range DNA sequence model for histone profile
• infercnvpy — Infercnv is a scalable python library to infer copy number variation (CNV) events from single cell transcriptomics data. It is heavliy inspired by InferCNV, but plays nicely with scanpy and is much more scalable.
• monkeybread — Analyze cellular niches in single-cell spatial transcriptomics data
• multimil — Multimodal weakly supervised learning to identify disease-specific changes in single-cell atlases
• nichejepa — Spatial omics foundation model
• Nimbus-Inference — A model for classification of cells into marker positive / negative
• ONTraC — A niche-centered, machine learning method for constructing spatially continuous trajectories
• pyclustree — Visualize cluster assignments at different resolutions
• pyLemur — A Python implementation of the LEMUR algorithm for analyzing multi-condition single-cell RNA-seq data.
• scanpy — Single-Cell Analysis in Python.
• scMDCF — Aligned Cross-modal Integration and Characterization of Single-Cell Multiomic Data with Deep Contrastive Learning
• scmorph — Single-cell morphological analysis
• scProject — Transfer learning framework for single cell gene expression analysis in Python
• scsims — Scalable, Interpretable Deep Learning for Single-Cell RNA-seq Classification
• scvi-criticism — Evaluation metrics for scvi-tools models
• session-info2 — Print versions of imported packages.
• simpler-flash — a simpler version of flashattention
• sobolev-alignment — Sobolev alignment of deep probabilistic models for comparing single cell profiles
• SpottedPy — Spatial hotspot analysis
• spVIPES — Shared-private Variational Inference with Product of Experts and Supervision
• StereoUtils — scanpy extra function for STOmics
• torchgmm — Run Gaussian Mixture Models on single or multiple CPUs/GPUs
• treedata — anndata with trees
• velocycle — Bayesian model for RNA velocity estimation of periodic manifolds