Deep probabilistic analysis of single-cell and spatial omics data
- scrna-seq
- variational-bayes
- variational-autoencoder
- cite-seq
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Deep probabilistic analysis of single-cell and spatial omics data
ADAM is a genomics analysis platform with specialized file formats built using Apache Avro, Apache Spark, and Apache Parquet. Apache 2 licensed.
Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis
Spatial Single Cell Analysis in Python
A Python Package for Protein Dynamics Analysis
[ICLR 2024] DNABERT-2: Efficient Foundation Model and Benchmark for Multi-Species Genome
Benchmarking analysis of data integration tools
Multi-Omics Factor Analysis
Reference mapping for single-cell genomics
Pan-Cancer Integrative Histology-Genomic Analysis via Multimodal Deep Learning - Cancer Cell
Haplotype-aware CNV analysis from single-cell RNA-seq, ATAC-seq, and multiome
MOGONET (Multi-Omics Graph cOnvolutional NETworks) is a novel multi-omics data integrative analysis framework for classification tasks in biomedical applications.
Open-source software for exploring and analyzing large, high-dimensional image-derived data.
Python package for image-based profiling
A tool for cell instance aware segmentation in densely packed 3D volumetric images
Integrated pipeline for multiplexed image analysis
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
Toolbox for the analysis of smFISH images.
NeuroAnatomy Toolbox: An R package for the (3D) visualisation and analysis of biological image data, especially tracings of single neurons.