bioRxiv / medRxiv
open access
FlashDeconv reveals resolution horizons in atlas-scale spatial transcriptomics
Coarsening Visium HD resolution from 8 to 64 m can flip cell-type co-localization from negative to positive (r = -0.12 [->] +0.80), yet many widely used compositional deconvolution workflows require coarsening or subsampling at million-bin scale. Here we introduce FlashDeconv, which combines leve
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- NicheDeSig: niche-aware deconvolution and adaptive signature analysis for spatial transcriptomics.#469365
- Benchmarking tools for deciphering cellular crosstalk in spatially-resolved transcriptomics.#185950
- Video Codec-Guided Training-Free Token Compression for Video Large Language Models#1297311
- jsPCA: fast, scalable, and interpretable identification of spatial domains and variable genes across multi-slice and multi-sample spatial transcriptomics data.#636326
- Deep Models, Shallow Alignment: Uncovering the Granularity Mismatch in Neural Decoding#662397
Record · ID 1278894
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive