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
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Biological foundation modeling from molecular to genome scale
Cloud-native genomic dataframes and batch computing
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
C library for high-throughput sequencing data formats
Foundation Models for Genomics & Transcriptomics
Precision Medicine Knowledge Graph (PrimeKG)
Official implementation for HyenaDNA, a long-range genomic foundation model built with Hyena
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
Fast, sensitive and accurate integration of single-cell data with Harmony
Spatial Single Cell Analysis in Python
R package for detecting doublets in single-cell RNA sequencing data
[ICLR 2024] DNABERT-2: Efficient Foundation Model and Benchmark for Multi-Species Genome
SCENIC is an R package to infer Gene Regulatory Networks and cell types from single-cell RNA-seq data.
Graph-linked unified embedding for single-cell multi-omics data integration
Benchmarking analysis of data integration tools
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Reference mapping for single-cell genomics
UCE is a zero-shot foundation model for single-cell gene expression data
Native R and Python sample-deletion robustness for omics: candidate certificates, minimum deletion bounds, Bioconductor model refits and donor-level pseudobulk
Schema and generated objects for biolink data model and upper ontology
A Python package for the identification, characterization and comparison of spatial clusters from spatial -omics data.