In marcocacciabue/Covidex:

This report was created using the Covidex vr version() software for subtyping of genome sequences.
Covidex can be accessed online at http://covidex.unlu.edu.ar/.

Covidex was built using RShiny by Marco Cacciabue and Pablo Aguilera.

If you use Covidex please consider citing the following preprint: https://www.biorxiv.org/content/10.1101/2020.08.21.261347v1

For more information please visit Covidex download site(https://sourceforge.net/projects/covidex/).

Run stats

Run was performed by user r input$user on r Sys.Date().
Input file r input$file[1,1] from which r as.character(length(data_reactive()$data_out$label)) sequences were selected for analysis.

Output table

The following table lists the sequences under analysis and the corresponding classification results.

# The `params` object is available in the document.

col<-brewer.pal(5,"Blues")
col2<-brewer.pal(5,"Reds")

table<-table()
  datatable(table,selection = 'single',
            extensions = 'Buttons',
            options = list(
               columnDefs = list(list(targets = c(8,9,10,12,14), visible = FALSE)),
              dom = 'Bfrtip',
              lengthMenu = list(c(5, 15, -1), c('5', '15', 'All')),
              pageLength = 15,
              buttons =
                list('copy', 'print', list(
                  extend = 'collection',
                  buttons = list(
                    list(extend = 'csv', filename = paste(input$file[1,1],"covidex_results"),sep=""),
                    list(extend = 'excel', filename = paste(input$file[1,1],"covidex_results"),sep=""),
                    list(extend = 'pdf', filename = paste(input$file[1,1],"covidex_results"),sep="")),
                  text = 'Download'
                )
                )
            ))%>% formatStyle("Rambaut","FLAG",
                     backgroundColor = styleEqual(c(0, 1), c(col[1], col[3])))%>% formatStyle("Length","Length_QC",
                     backgroundColor = styleEqual(c(0, 1), c(col2[3], col2[1])))%>% formatStyle("N","N_QC",
                     backgroundColor = styleEqual(c(0, 1), c(col2[3], col2[1]))) 

Variants of Concern report

r as.character((sum(data_reactive()$data_out$VOC==TRUE))) of the r as.character(length(data_reactive()$data_out$label)) sequences in the analysis were labeled as putative VOC variants. In this sense, the following pie chart shows the percentage of VOC variants detected (true=VOC, false=non-VOC).

# The `params` object is available in the document.

table<-table()
data<-data.frame(Rambaut=table$Rambaut,VOC=table$VOC)
plot_ly(data,labels = ~VOC,type = 'pie')
if (sum(data$VOC)>0){
data<-data[data$VOC==TRUE,]
plot_ly(data,labels = ~Rambaut,type = 'pie')
}

Variants of Interest report

r as.character((sum(data_reactive()$data_out$VOI==TRUE))) of the r as.character(length(data_reactive()$data_out$label)) sequences in the analysis were labeled as putative VOI variants. In this sense, the following pie chart shows the percentage of VOI variants detected (true=VOI, false=non-VOI).

# The `params` object is available in the document.

table<-table()
data<-data.frame(Rambaut=table$Rambaut,VOI=table$VOI)
plot_ly(data,labels = ~VOI,type = 'pie')
if (sum(data$VOI)>0){
data<-data[data$VOI==TRUE,]
plot_ly(data,labels = ~Rambaut,type = 'pie',marker = list(colors = c('#FF7F0E', '#1F77B4')))
}

Variants of concern (VOC) and variants of Interest (VOI) are defined accorded to https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/variant-surveillance/variant-info.html

Classification models

The following table lists the models used for the classification.

# The `params` object is available in the document.

model_data<-model_table()
  datatable(model_data)

marcocacciabue/Covidex documentation built on March 24, 2021, 11:51 a.m.