From 1575cd5b2cf6abeb9af70ceb49533f620e1e6ebb Mon Sep 17 00:00:00 2001
From: Lieke Michielsen <42767830+lcmmichielsen@users.noreply.github.com>
Date: Thu, 18 Apr 2024 13:54:27 +0200
Subject: [PATCH] Update README.rst

---
 README.rst | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/README.rst b/README.rst
index 9946951..bbf31dd 100644
--- a/README.rst
+++ b/README.rst
@@ -1,11 +1,11 @@
-|PyPI| |PyPIDownloads| |Docs|
+.. raw:: html
 
-scHPL: Hierarchical progressive learning of cell identities in single-cell data
+ <img src="https://github.com/lcmmichielsen/scHPL/blob/master/docs/scHPL.png" width="820px" align="center">
 
+|PyPI| |PyPIDownloads| |Docs|
 
-.. raw:: html
 
- <img src="https://github.com/lcmmichielsen/scHPL/blob/master/docs/scHPL.png" width="820px" align="center">
+scHPL: Hierarchical progressive learning of cell identities in single-cell data
 
 We present a hierarchical progressive learning method which automatically finds relationships between cell populations across multiple datasets and uses this to construct a hierarchical classification tree. For each node in the tree either a linear SVM, kNN, or one-class SVM, which enables the detection of unknown populations, is trained. The trained classification tree can be used to predict the labels of a new unlabeled dataset.