ReadME Updates

README.Rmd

@@ -13,7 +13,7 @@ knitr::opts_chunk$set(
 )
 ```
 
-# STew <img width="43%" align = "right" src="https://github.com/fanzhanglab/STew/blob/main/STew_logo.png">
+# STew <img width="43%" align = "right" src="https://github.com/fanzhanglab/STew/blob/main/STewlogo.png">
 
 [![R-CMD-check](https://github.com/fanzhanglab/STew/actions/workflows/check-standard.yaml/badge.svg)](https://github.com/fanzhanglab/STew/actions/workflows/check-standard.yaml)
 ![](https://komarev.com/ghpvc/?username=fanzhanglab&style=flat-square&color=green)

README.md

@@ -1,42 +1,42 @@
 
 <!-- README.md is generated from README.Rmd. Please edit that file -->
 
-# stCCA <img width="43%" align = "right" src="https://github.com/fanzhanglab/stCCA/blob/main/stCCA_logo.png">
+# STew <img width="43%" align = "right" src="https://github.com/fanzhanglab/STew/blob/main/STewlogo.png">
 
-[![R-CMD-check](https://github.com/fanzhanglab/stCCA/actions/workflows/check-standard.yaml/badge.svg)](https://github.com/fanzhanglab/stCCA/actions/workflows/check-standard.yaml)
+[![R-CMD-check](https://github.com/fanzhanglab/STew/actions/workflows/check-standard.yaml/badge.svg)](https://github.com/fanzhanglab/STew/actions/workflows/check-standard.yaml)
 ![](https://komarev.com/ghpvc/?username=fanzhanglab&style=flat-square&color=green)
 
 <!-- badges: start -->
 <!-- badges: end -->
 <p align="justify">
-We introduce stCCA, a multi-view representation learning method for
+We introduce STew, a multi-view representation learning method for
 spatial transcriptomic data, to jointly characterize the gene expression
 variation and spatial information in the shared low-dimenion space in a
-scalable manner. stCCA will output distinct spatially informed cell
+scalable manner. STew will output distinct spatially informed cell
 gradients, robust clusters, and statistical goodness of model fit to
 reveal significant genes that reflect subtle spatial niches in complex
 tissues.
 </p>
 
-<img width="100%" align = "center" src="https://github.com/fanzhanglab/stCCA/blob/main/man/figures/Figure1.png">
+<img width="100%" align = "center" src="https://github.com/fanzhanglab/STew/blob/main/man/figures/Figure1.png">
 
 </br>
 
 ## Installation
 
-You can install the stCCA Package from
-[GitHub](https://github.com/fanzhanglab/stCCA/) using the devtools as
+You can install the STew Package from
+[GitHub](https://github.com/fanzhanglab/STew/) using the devtools as
 follows:
 
 ``` r
 # install.packages("devtools")
-devtools::install_github("fanzhanglab/stCCA")
+devtools::install_github("fanzhanglab/STew")
 ```
 
 (OR)
 
 ``` r
-remotes::install_github("fanzhanglab/stCCA")
+remotes::install_github("fanzhanglab/STew")
 ```
 
 <br/>
@@ -59,90 +59,89 @@ remotes::install_github("fanzhanglab/stCCA")
 
 ## Tutorials
 
-**Step-by-step notebook** of applying stCCA on identifying spatially
+**Step-by-step notebook** of applying STew on identifying spatially
 informed low-dimensional embeddings and spatially aware clusters on the
 10X Visium Human Brain Data (DLPFC):
 
-- <a href="https://htmlpreview.github.io/?https://github.com/fanzhanglab/stCCA/blob/main/vignettes/Tutorial_stCCA_DLPFC.html">
-  Tutorial of applying stCCA on DLPFC data </a>
-- <a href = 'https://htmlpreview.github.io/?https://github.com/fanzhanglab/stCCA/blob/main/vignettes/count_modeling_tutorial_dlfcp.nb.html'>
+- <a href="https://htmlpreview.github.io/?https://github.com/fanzhanglab/STew/blob/main/vignettes/Tutorial_STew_DLPFC.html">
+  Tutorial of applying STew on DLPFC data </a>
+- <a href = 'https://htmlpreview.github.io/?https://github.com/fanzhanglab/STew/blob/main/vignettes/count_modeling_tutorial_dlfcp.nb.html'>
   Tutorial of count data modelling </a>
 
 <br/>
 
-#### Below are several major steps of running stCCA:
+#### Below are several major steps of running STew:
 
 ``` r
-# Create a new stCCA object for the loaded spatial transcriptomic data
-stCCA = stCCA_Obj(count = dlpfc$count_exp,
+# Create a new STew object for the loaded spatial transcriptomic data
+STew = STew_Obj(count = dlpfc$count_exp,
                   spatial = dlpfc$spatial)
 ```
 
 … (skip several preprocessing steps) …
 
 ``` r
 # permute optimal penalty parameters
-stCCA <- parallel_cca_permute(x = stCCA$exp_adj_matrix, z = stCCA$adj_matrix, obj = stCCA, nperms=50, niter=3)
+STew <- parallel_cca_permute(x = STew$exp_adj_matrix, z = STew$adj_matrix, obj = STew, nperms=50, niter=3)
 ```
 
 ``` r
 # Perform sparse CCA based on the optimal penalty parameters
-stCCA <- cca_main(x = stCCA$exp_adj_matrix, z = stCCA$adj_matrix, obj = stCCA, K=20, penaltyx=stCCA$bestpenaltyx, penaltyz=stCCA$bestpenaltyz, v=stcc$v.init)
+STew <- cca_main(x = STew$exp_adj_matrix, z = STew$adj_matrix, obj = STew, K=20, penaltyx=STew$bestpenaltyx, penaltyz=STew$bestpenaltyz, v=STew$v.init)
 ```
 
 ``` r
-gradient_plot <- spatial_gradient(stCCA)
+gradient_plot <- spatial_gradient(STew)
 gradient_plot[1:5]
 ```
 
-<img width="85%" align = "center" src="https://github.com/fanzhanglab/stCCA/blob/main/man/figures/cca_vis.png">
+<img width="85%" align = "center" src="https://github.com/fanzhanglab/STew/blob/main/man/figures/cca_vis.png">
 
 <br/>
 
 ``` r
-cluster_plot <- plot_cluster(coordis = spatial, label = cluster$res_0.30, colors = colors, t="Cell clusters based on stCCA")
+cluster_plot <- plot_cluster(coordis = spatial, label = cluster$res_0.30, colors = colors, t="Cell clusters based on STew")
 cluster_plot
 ```
 
-<img width="25%" align = "center" src="https://github.com/fanzhanglab/stCCA/blob/main/man/figures/README-unnamed-chunk-14-1.png">
+<img width="25%" align = "center" src="https://github.com/fanzhanglab/STew/blob/main/man/figures/README-unnamed-chunk-14-1.png">
 
 <br/>
 
 ``` r
-# Save the main results into the stCCA object
-saveRDS(stCCA, file="stCCA_10x_human_dlpfc_no.rds")
+# Save the main results into the STew object
+saveRDS(STew, file="STew_10x_human_dlpfc_no.rds")
 ```
 
 <br/>
 
-#### Benchmarcking stCCA with other algorithms:
+#### Benchmarcking STew with other algorithms:
 
-<img width="85%" align = "center" src="https://github.com/fanzhanglab/stCCA/blob/main/man/figures/ARI_DLPFC.png">
+<img width="85%" align = "center" src="https://github.com/fanzhanglab/STew/blob/main/man/figures/ARI_DLPFC.png">
 
 <br/>
 
 ## Citations
 
 Guo, N., Vargas, J., Fritz, D., Krishna, R., Zhang, F. Uncover spatially
 informed shared variations underlying single-cell spatial
-transcriptomics with stCCA, [*bioRxiv*](link), 2023
+transcriptomics with STew, [*bioRxiv*](link), 2023
 
 <br/>
 
 ## Help, Suggestion and Contribution
 
-Using github [**issues**](https://github.com/fanzhanglab/stCCA/issues)
+Using github [**issues**](https://github.com/fanzhanglab/STew/issues)
 section, if you have any question, comments, suggestions, or to report
-coding related issues of stCCA is highly encouranged than sending
-emails.
+coding related issues of STew is highly encouranged than sending emails.
 
 - Please **check the GitHub
-  [issues](https://github.com/fanzhanglab/stCCA/issues)** for similar
+  [issues](https://github.com/fanzhanglab/STew/issues)** for similar
   issues that has been reported and resolved. This helps the team to
   focus on adding new features and working on cool projects instead of
   resolving the same issues!
 - **Examples** are required when filing a GitHub issue. In certain
-  cases, please share your stCCA object and related codes to understand
+  cases, please share your STew object and related codes to understand
   the issues.
 
 <br/>