From af45c9b239fd3f3a54b37e56d9a556fb2f224a51 Mon Sep 17 00:00:00 2001
From: Chen Yang <cafferychen777@tamu.edu>
Date: Tue, 6 Jan 2026 16:05:53 -0600
Subject: [PATCH 1/2] Add FlashDeconv to ecosystem packages

---
 packages/flashdeconv/meta.yaml | 27 +++++++++++++++++++++++++++
 1 file changed, 27 insertions(+)
 create mode 100644 packages/flashdeconv/meta.yaml

diff --git a/packages/flashdeconv/meta.yaml b/packages/flashdeconv/meta.yaml
new file mode 100644
index 0000000..326b1c4
--- /dev/null
+++ b/packages/flashdeconv/meta.yaml
@@ -0,0 +1,27 @@
+name: flashdeconv
+description: |
+  FlashDeconv is a high-performance spatial transcriptomics deconvolution tool that enables cell type mapping
+  at atlas scale. Using structure-preserving sketching via randomized numerical linear algebra, FlashDeconv
+  achieves linear time and memory complexity, processing 1 million spots in approximately 3 minutes on a
+  standard laptop without GPU. It provides accurate cell type proportion estimation with Pearson r = 0.944
+  on the Spotless benchmark, and preserves rare cell type detection through leverage-score weighted sampling.
+project_home: https://github.com/cafferychen777/flashdeconv
+documentation_home: https://flashdeconv.readthedocs.io/
+tutorials_home: https://flashdeconv.readthedocs.io/
+publications:
+  - 10.64898/2025.12.22.696108
+install:
+  pypi: flashdeconv
+tags:
+  - spatial transcriptomics
+  - deconvolution
+  - cell type
+  - Visium HD
+  - sketching
+license: BSD-3-Clause
+version: v0.1
+contact:
+  - cafferychen777
+test_command: |
+  pip install ".[test]" && pytest
+category: ecosystem

From 442aeb296832127c87b3aded2e075cd0274884f4 Mon Sep 17 00:00:00 2001
From: Chen Yang <cafferychen777@tamu.edu>
Date: Tue, 6 Jan 2026 16:39:06 -0600
Subject: [PATCH 2/2] Fix documentation URLs to use GitHub instead of
 readthedocs

---
 packages/flashdeconv/meta.yaml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/packages/flashdeconv/meta.yaml b/packages/flashdeconv/meta.yaml
index 326b1c4..77cf36a 100644
--- a/packages/flashdeconv/meta.yaml
+++ b/packages/flashdeconv/meta.yaml
@@ -6,8 +6,8 @@ description: |
   standard laptop without GPU. It provides accurate cell type proportion estimation with Pearson r = 0.944
   on the Spotless benchmark, and preserves rare cell type detection through leverage-score weighted sampling.
 project_home: https://github.com/cafferychen777/flashdeconv
-documentation_home: https://flashdeconv.readthedocs.io/
-tutorials_home: https://flashdeconv.readthedocs.io/
+documentation_home: https://github.com/cafferychen777/flashdeconv#readme
+tutorials_home: https://github.com/cafferychen777/flashdeconv/tree/main/examples
 publications:
   - 10.64898/2025.12.22.696108
 install: