readjust

Author: JGarnica22

README.md

@@ -2,7 +2,7 @@
 
 <p align="center">
 
-<img src="docs/HiTME_logo.png" height="100"/>
+<img src="docs/HiTME_logo.png" height="140"/>
 
 </p>
 
@@ -12,30 +12,36 @@ HiTME is designed for precise cell type classification within the complex tumor
 
 Find a vignette describing its main functions in [html](https://carmonalab.github.io/HiTME_CaseStudies/HiTME_GetStarted.html) and its [code (repository)](https://github.com/carmonalab/HiTME_CaseStudies).
 
+<br>
+
 ## Installation
 
 ``` r
 # install.packages("remotes")
 remotes::install_github("carmonalab/HiTME")
 ```
 
+<br>
+
 ## Usage
 
 ``` r
 library(ProjecTILs)
 library(HiTME)
 
 # Fetch reference maps
-ref.maps <- ref.maps <- get.reference.maps(collection = "human")
+ref.maps <- get.reference.maps(collection = "human")
 
 # Cell type classification on a Seurat object
 query <- Run.HiTME(query,
                    ref.maps = ref.maps[["human"]])
 
-# Seurat object metadata has been updated with cell type classification at different granularity levels (layers)
+# Seurat object metadata has been updated with cell type classification at
+# different granularity levels (layers)
 ```
+<br>
 
-### How to cite HiTME
+## How to cite HiTME
 Please note that the publication describing HiTME is currently in preparation. In the meantime, we kindly ask that you cite the two primary components of HiTME in your work:
 
 - [scGate](https://github.com/carmonalab/scGate): Andreatta, Massimo, Ariel J. Berenstein, and Santiago J. Carmona. 2022. “scGate: Marker-Based Purification of Cell Types from Heterogeneous Single-Cell RNA-Seq Datasets.” Bioinformatics 38 (April): 2642–44. https://doi.org/10.1093/BIOINFORMATICS/BTAC141.