Merge branch 'main' of https://github.com/KaiyanM/MolPad

DESCRIPTION

@@ -3,10 +3,9 @@ Title: MolPad: An R-Shiny Package for Cluster Co-Expression Analysis in Longitud
 Version: 1.0.0
 Authors@R: 
     person("Kaiyan", "Ma", , "[email protected]", role = c("aut", "cre"),
-           comment = c(ORCID = "YOUR-ORCID-ID"))
+           comment = c(ORCID = "0000-0002-7355-8924"))
 Description: MolPad offers a visualization dashboard tool designed to enhance our understanding of how molecular co-expression works in the context of multi-omics microbiome data. The approach involves using a cluster network to provide an initial overview of relationships across multiple omics, with the added functionality to interactively zoom in on specific areas of interest. To facilitate this analysis, we've developed a focus-plus-context strategy that seamlessly connects to online curated annotations.
-License: `use_mit_license()`, `use_gpl3_license()` or friends to pick a
-    license
+License: `use_mit_license()`, `use_gpl3_license()` or friends to pick a license
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.2.3

paper/paper.md

@@ -18,10 +18,6 @@ authors:
   - name: Author with no affiliation
     corresponding: true # (This is how to denote the corresponding author)
     affiliation: 3
-  - given-names: Ludwig
-    dropping-particle: van
-    surname: Beethoven
-    affiliation: 3
 affiliations:
  - name: University of Wisconsin-Madison, USA
    index: 1
@@ -60,13 +56,13 @@ In applying the dashboard, we made an extended time series by connecting the las
 
 # Usage
 
-The source code for `MolPad` is stored on [Github](https://github.com/KaiyanM/MolPad). The app is hosted in the eponymous R package which can be downloaded and run on a local computer. We anticipate that some users may need more flexibility in their analyses, requiring backend R coding for tasks like setting up detailed operating models or download figure outputs. For such needs, the essential set of R functions employed in the Shiny app is accessible through the R package.
+The source code for `MolPad` is stored on [Github](https://github.com/KaiyanM/MolPad). The app is hosted in the eponymous R package which can be downloaded and run on a local computer. We anticipate that some users may need more flexibility in their analyses, requiring backend R coding for tasks like setting up detailed operating models or downloading figure outputs. For such needs, the essential set of R functions employed in the Shiny app is accessible through the R package.
 
 # Figures
 
 ![Dashboard Overview: `A`: cluster-level network, `B`: taxonomic-level bar plot, `C`:  a type-level line plot, and `D`: a feature-level table. \label{fig:dashboard}](dashboard.png)
 
-![Example of discoversing related patterns with network plot. For `a`, the two linked nodes are in the dashed box and have a closer inverse pattern than the other. For `b`, these groups are both less volatile on average and have similar inverse patterns.\label{fig:pattern}](pattern.png){ width=50% }
+![Example of discovering related patterns with network plot. For `a`, the two linked nodes are in the dashed box and have a closer inverse pattern than the other. For `b`, these groups are both less volatile on average and have similar inverse patterns.\label{fig:pattern}](pattern.png){ width=60% }
 
 ![Dashboard showing Groups 10, 7, 4, and 3 for the
 bacterial(a.) and Group 4 for the eukaryotic(b.) community. Groups 10 and 4 have decreasing trends for both cheeses, and they all include largely Proteobacteria and Firmicutes. While Groups 3 and 7 have the opposite increasing trends, which include more Actinobacteria and Bacteroidetes. Among these, Groups 7 and 4 have the strongest periodicity, suggesting a more reproducible tendency for the corresponding main components. For the eukaryote community, most of the features followed the same stable pattern as in Group 4\label{fig:cheesecase}](cheesecase.png){ width=80% }