Update authors and README

neurogenomics · Jun 18, 2024 · a12b9c2 · a12b9c2
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -3,11 +3,18 @@ Type: Package
 Title: Benchmarking Epigenomic Profiling Methods Using Motif Enrichment
 Version: 0.99.0
 Authors@R: c( 
-     person(given = "Hiranyamaya",
-           family = "Dash",
-           role = c("cre", "aut"),
-           email = "hdash.work@gmail.com",
-           comment = c(ORCID = "0009-0005-5514-505X"))
+    person(given = "Hiranyamaya",
+        family = "Dash",
+        role = c("cre", "aut"),
+        email = "hdash.work@gmail.com",
+        comment = c(ORCID = "0009-0005-5514-505X")),
+    person(given="Thomas", family="Roberts",
+        email = "tomroberts.work15@gmail.com",
+        role = "aut"),
+    person(given="Nathan", family="Skene", 
+        email = "nathan.skene@gmail.com", 
+        role = "aut",
+        comment = c(ORCID = "0000-0002-6807-3180"))
     )
 Description: MotifPeeker is used to compare and analyse datasets from epigenomic
   profiling methods with motif enrichment as the key benchmark. 

diff --git a/README.Rmd b/README.Rmd
@@ -1,7 +1,7 @@
 ---
-title: "`r read.dcf('DESCRIPTION', fields = 'Package')[1]`"  
+title: "<code>MotifPeeker</code><br>Benchmarking Epigenomic Profiling Methods Using Motif Enrichment"  
 author: "`r rworkflows::use_badges()`" 
-date: "<h4>README updated: <i>`r format( Sys.Date(), '%b-%d-%Y')`</i></h4>"
+date: "<h4>Updated: <i>`r format( Sys.Date(), '%b-%d-%Y')`</i></h4>"
 output:
   github_document
 ---
@@ -15,16 +15,36 @@ owner <- strsplit(URL,"/")[[1]][4]
 repo <- strsplit(URL,"/")[[1]][5]
 ```
 
-## ``r pkg``: `r gsub("\n","",title)`
 
-### `r gsub("\n","",description)`
+# Introduction
+
+`MotifPeeker` is used to compare and analyse datasets from epigenomic
+profiling methods with motif enrichment as the key benchmark. The package
+outputs an HTML report consisting of three sections:  
+
+1. **General Metrics**: Overview of peaks-related general metrics for the
+datasets (FRiP scores, peak widths and motif-summit distances). 
+2. **Known Motif Enrichment Analysis**: Statistics for the frequency of
+user-provided motifs enriched in the datasets. 
+3. **De-Novo Motif Enrichment Analysis**: Statistics for the frequency of
+de-novo discovered motifs enriched in the datasets and compared with known
+motifs. 
 
 <!-- If you use ``r pkg``, please cite:  -->
 
 <!-- > `r utils::citation(pkg)$textVersion` -->
 
-## Installation 
+# Installation 
+
+`MotifPeeker` uses
+[`memes`](https://www.bioconductor.org/packages/release/bioc/html/memes.html)
+which relies on a local install of the
+[MEME suite](https://meme-suite.org/meme/). Installation instructions can be
+found [here](https://www.bioconductor.org/packages/release/bioc/vignettes/memes/inst/doc/install_guide.html).
+
 
+Once the MEME suite is installed, `MotifPeeker` can be installed using the
+following code:
 ```R
 if(!require("remotes")) install.packages("remotes")
 

diff --git a/README.md b/README.md
@@ -1,4 +1,5 @@
-MotifPeeker
+<code>MotifPeeker</code><br>Benchmarking Epigenomic Profiling Methods
+Using Motif Enrichment
 ================
 <img src='https://github.com/neurogenomics/MotifPeeker/raw/master/inst/hex/hex.png' title='Hex sticker for MotifPeeker' height='300'><br>
 [![License:
@@ -15,17 +16,37 @@ status](https://github.com/neurogenomics/MotifPeeker/workflows/rworkflows/badge.
 Authors: <i>Hiranyamaya Dash</i>  
 </h4>
 <h4>  
-README updated: <i>Jun-18-2024</i>  
+Updated: <i>Jun-18-2024</i>  
 </h4>
 
-## `MotifPeeker`: Benchmarking Epigenomic Profiling Methods Using Motif Enrichment
+# Introduction
 
-### MotifPeeker is used to compare and analyse datasets from epigenomic profiling methods with motif enrichment as the key benchmark. The package outputs an HTML report consisting of three sections: (1. General Metrics) Overview of peaks-related general metrics for the datasets (FRiP scores, peak widths and motif-summit distances). (2. Known Motif Enrichment Analysis) Statistics for the frequency of user-provided motifs enriched in the datasets. (3. De-Novo Motif Enrichment Analysis) Statistics for the frequency of de-novo discovered motifs enriched in the datasets and compared with known motifs.
+`MotifPeeker` is used to compare and analyse datasets from epigenomic
+profiling methods with motif enrichment as the key benchmark. The
+package outputs an HTML report consisting of three sections:
+
+1.  **General Metrics**: Overview of peaks-related general metrics for
+    the datasets (FRiP scores, peak widths and motif-summit distances).
+2.  **Known Motif Enrichment Analysis**: Statistics for the frequency of
+    user-provided motifs enriched in the datasets.
+3.  **De-Novo Motif Enrichment Analysis**: Statistics for the frequency
+    of de-novo discovered motifs enriched in the datasets and compared
+    with known motifs.
 
 <!-- If you use `MotifPeeker`, please cite:  -->
-<!-- > author1, author2, author3 (publicationYear) articleTitle, *journalName*; volumeNumber, [linkToPublication](linkToPublication) -->
+<!-- >  -->
+
+# Installation
+
+`MotifPeeker` uses
+[`memes`](https://www.bioconductor.org/packages/release/bioc/html/memes.html)
+which relies on a local install of the [MEME
+suite](https://meme-suite.org/meme/). Installation instructions can be
+found
+[here](https://www.bioconductor.org/packages/release/bioc/vignettes/memes/inst/doc/install_guide.html).
 
-## Installation
+Once the MEME suite is installed, `MotifPeeker` can be installed using
+the following code:
 
 ``` r
 if(!require("remotes")) install.packages("remotes")
@@ -69,19 +90,20 @@ utils::sessionInfo()
     ## 
     ## loaded via a namespace (and not attached):
     ##  [1] gtable_0.3.5        jsonlite_1.8.8      renv_1.0.7         
-    ##  [4] compiler_4.4.1      BiocManager_1.30.23 rvcheck_0.2.1      
-    ##  [7] scales_1.3.0        yaml_2.3.8          fastmap_1.2.0      
-    ## [10] here_1.0.1          ggplot2_3.5.1       R6_2.5.1           
-    ## [13] knitr_1.47          yulab.utils_0.1.4   tibble_3.2.1       
-    ## [16] desc_1.4.3          dlstats_0.1.7       rprojroot_2.0.4    
-    ## [19] munsell_0.5.1       pillar_1.9.0        RColorBrewer_1.1-3 
-    ## [22] rlang_1.1.4         utf8_1.2.4          cachem_1.1.0       
-    ## [25] badger_0.2.4        xfun_0.45           fs_1.6.4           
-    ## [28] memoise_2.0.1       cli_3.6.2           magrittr_2.0.3     
-    ## [31] rworkflows_1.0.1    digest_0.6.35       grid_4.4.1         
-    ## [34] rstudioapi_0.16.0   lifecycle_1.0.4     vctrs_0.6.5        
-    ## [37] evaluate_0.24.0     glue_1.7.0          data.table_1.15.4  
-    ## [40] fansi_1.0.6         colorspace_2.1-0    rmarkdown_2.27     
-    ## [43] tools_4.4.1         pkgconfig_2.0.3     htmltools_0.5.8.1
+    ##  [4] dplyr_1.1.4         compiler_4.4.1      BiocManager_1.30.23
+    ##  [7] tidyselect_1.2.1    rvcheck_0.2.1       scales_1.3.0       
+    ## [10] yaml_2.3.8          fastmap_1.2.0       here_1.0.1         
+    ## [13] ggplot2_3.5.1       R6_2.5.1            generics_0.1.3     
+    ## [16] knitr_1.47          yulab.utils_0.1.4   tibble_3.2.1       
+    ## [19] desc_1.4.3          dlstats_0.1.7       rprojroot_2.0.4    
+    ## [22] munsell_0.5.1       pillar_1.9.0        RColorBrewer_1.1-3 
+    ## [25] rlang_1.1.4         utf8_1.2.4          cachem_1.1.0       
+    ## [28] badger_0.2.4        xfun_0.45           fs_1.6.4           
+    ## [31] memoise_2.0.1       cli_3.6.2           magrittr_2.0.3     
+    ## [34] rworkflows_1.0.1    digest_0.6.35       grid_4.4.1         
+    ## [37] rstudioapi_0.16.0   lifecycle_1.0.4     vctrs_0.6.5        
+    ## [40] data.table_1.15.4   evaluate_0.24.0     glue_1.7.0         
+    ## [43] fansi_1.0.6         colorspace_2.1-0    rmarkdown_2.27     
+    ## [46] tools_4.4.1         pkgconfig_2.0.3     htmltools_0.5.8.1
 
 </details>