@kennypavan's AnnSQL software for facile, lightning-fast analysis of large-scale scRNA-seq datasets is out now in @BioinfoAdv. >19k downloads thus far and we'd love to grow the developer base. Easily analyze millions of RNA profiles from your laptop. No HPC necessary!
Let's talk about inte𝗥operability. The Python based AnnSQL package creates shareable databases from AnnData objects. Using the DuckDB R package, you can easily open these databases and query the database 🧬🖥️ #SingleCell#R#bioinformatics#DuckDB
https://t.co/uJfxL8mupX
Our latest work in collaboration with the Bourhy Lab (Pasteur Inst.) in which we use scRNA-seq to characterize host-rabies molecular interactions across diverse human brain cell types. Recommended if you're interested in "system virology" or glial biology: https://t.co/jPhuG3z3SL
New feature in #AnnSQL!
Easily create meta cell views for massive single-cell datasets. In this example: 600k cells are grouped by type & age to provide a summary of molecular diversity.
Live long and analyze🖖#Bioinformatics#DuckDb#Genomics
https://t.co/EbMaVhLYYt
With AnnSQL, the needs of the many cells outweigh the needs of the few. Achieve warp-speed insights across millions of data points! 🖖#spock#bioinformatics#datascience#duckdb#annsql
https://t.co/njSqBSpm26
We pushed AnnSQL to its limits with a 4.4 million-cell mouse brain dataset 🧠 and it excelled! Filtering alone was 680x faster than standard filtering of AnnData on a laptop.
Struggling with AnnData? Meet AnnSQL, our python package for lightning-fast scRNA-seq analysis:
https://t.co/Le6NMxwtJc
AnnSQL achieves ~700x runtime improvements over AnnData, enabling datasets with millions of cells to be queried in minutes on a laptop using elegant SQL syntax.