Nothing
InSilico Sequencing Report
In SNPannotator: Investigating the Functional Characteristics of Selected SNPs and Their Vicinity Genomic Region
varCount = max(output$`#gSNP`)
makeReport_LD <- function(var.data) {
# find unique gene names
genes=var.data$Gene
genes= strsplit(trimws(genes), ",\\s*")
genes =unlist(genes)
genes = gsub(x = genes,pattern = '(.+)(\\(.+\\))',replacement = '\\1')
genes= paste(sort(unique(genes)),collapse = ', ')
# associations
assoc=var.data$Associations
assoc= strsplit(trimws(assoc), ",\\s*")
assoc =sort(unique(unlist(assoc)))
# report
gsnp.data = var.data[gSNP == Linked_SNP,]
# starting <div>
cat(sprintf('<div id="variant%s">',gsnp.data$`#gSNP`))
cat(sprintf('<span class="topic">Variant ID:</span> <span class="value">%s</span><br/>', gsnp.data$gSNP))
cat(sprintf('<span class="topic">Position: </span> <span class="value">%s:%s (%s)</span><br/>', gsnp.data$Chr, gsnp.data$Pos_37, gsnp.data$Cytoband))
cat(sprintf('<span class="topic">Alleles: </span> <span class="value">%s (%s)</span><br/>', gsnp.data$`Alleles in population`, gsnp.data$`Allele frequencies`))
cat(sprintf('<span class="topic">Type: </span> <span class="value">%s</span><br/>', tools::toTitleCase(gsub(x = gsnp.data$Type,pattern = '_',replacement = ' '))))
cat(sprintf('<span class="topic">Proxy Variants: </span> <span class="value">%s </span><br/>', nrow(var.data)-1))
cat('<br/><span class="topic">Mapped genes</span>')
cat(kableExtra::kable(genes,format = 'html',col.names = NULL))
if(length(assoc) > 15 & length(assoc) %% 2 == 0)
{
assoc=cbind(assoc[1:(length(assoc)/2)],
assoc[((length(assoc)/2) +1 ):length(assoc)])
} else if (length(assoc) > 15 & length(assoc) %% 2 != 0)
{
assoc=cbind(assoc[1:(ceiling(length(assoc)/2))],
c(assoc[(ceiling((length(assoc)/2))+1):length(assoc)],''))
}
if(length(assoc)>1)
{
cat('<br/><span class="topic">Associated phenotypes</span>')
cat(kableExtra::kable(assoc,format = 'html', col.names = NULL,booktabs = TRUE) %>%
kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"),
full_width = F,
position = "left"))
}
cat('<br/>')
cat(kableExtra::kable(var.data[,.N,by=Type],format = 'html',col.names = c('type','count'),caption = '<span class="topic">Variant types</span>')%>%
kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"),
full_width = F,
position = "left") %>%
kableExtra::column_spec(1, bold = TRUE, border_right = TRUE,width="15em") %>%
kableExtra::column_spec(2, width="10em"))
cat('<br/>')
cat('<br/>')
if(var.data[gSNP!=Linked_SNP & Type=='missense_variant',.N] > 0)
cat(kableExtra::kable(var.data[gSNP!=Linked_SNP & Type=='missense_variant', list(Linked_SNP,LD,Gene)],format = 'html',col.names = c('rsID','LD','Gene'),caption = '<span class="topic">Missense variants</span>')%>%
kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"),
full_width = F,
position = "left") %>%
kableExtra::column_spec(1, bold = TRUE, border_right = TRUE,width="10em") %>%
kableExtra::column_spec(2, width="10em", border_right = TRUE,extra_css = 'text-align:left;') %>%
kableExtra::column_spec(3, width="15em"))
cat('<br/>')
cat('<br/>')
if(nrow(var.data) > 1)
{
mis.var <- var.data[gSNP!=Linked_SNP & Type=='missense_variant',.N] > 0
plot(
ggplot2::ggplot() +
ggplot2::geom_point(data = var.data[gSNP!=Linked_SNP & Type!='missense_variant',],mapping = aes(x=Pos_37 , y=LD,color=LD),size=3) +
ggplot2::geom_point(data = var.data[gSNP!=Linked_SNP & Type=='missense_variant',],mapping = aes(x=Pos_37 , y=LD),size=3,shape=10,color='black',stroke=1.5) +
ggplot2::geom_text(data = var.data[gSNP!=Linked_SNP & Type=='missense_variant',],
mapping = aes(x=Pos_37 , y=LD,label=Linked_SNP),
hjust=-.3) +
ggplot2::geom_point(data = var.data[gSNP==Linked_SNP,],mapping = aes(x=Pos_37 , y=LD),
color='black',shape=17,size=4) +
ggplot2::labs(title = "Regional plot", x = "Position",y= expression(LD (R^2))) +
ggplot2::scale_y_continuous(limits = c(r2 ,1.035))+
ggplot2::scale_x_continuous(limits = c(gsnp.data$Pos_37-(window_size*1000) ,gsnp.data$Pos_37+(window_size*1000)))+
ggplot2::scale_color_gradient2(low = "darkblue",mid = "orange",high = "darkred",midpoint = ((1+r2)/2), limits=c(r2,1)) +
ggplot2::annotate(geom='text',x=gsnp.data$Pos_37,y=1.035,label=gsnp.data$gSNP) + {
if(mis.var)
ggplot2::annotate(geom='text',x=gsnp.data$Pos_37+420000,y=.98,label='missense variant')
}+{
if(mis.var)
ggplot2::geom_point(aes(x=gsnp.data$Pos_37+320000, y= 0.975),size=3,shape=10,color='black',stroke=1.5)
}+{
if(mis.var)
ggplot2::geom_rect(mapping=aes(xmin = gsnp.data$Pos_37+300000,
xmax = gsnp.data$Pos_37+500000,
ymin=.95,
ymax=1),color='black',alpha=0)
}+
ggplot2::theme_light() +
ggplot2::theme(legend.position = c(0.1,0.7)))
}
cat('</div><br/><br/><br/><hr/>')
}
makeReport_CADD <- function(var.data) {
# find unique gene names
genes=var.data$Gene
genes= strsplit(trimws(genes), ",\\s*")
genes =unlist(genes)
genes = gsub(x = genes,pattern = '(.+)(\\(.+\\))',replacement = '\\1')
genes= paste(sort(unique(genes)),collapse = ', ')
# associations
assoc=var.data$Associations
assoc= strsplit(trimws(assoc), ",\\s*")
assoc =sort(unique(unlist(assoc)))
# check if CADD score exists and correct it
has.cadd <- FALSE
max.cadd <- NULL
if(is.element('cadd',names(var.data)))
{
var.data[,cadd.score := ifelse(!grepl(x = cadd,pattern = ','),
sub(x = cadd,pattern = "(.+) = (.+)",replacement = '\\2'),
NA),
by=Linked_SNP]
var.data$cadd.score <- as.numeric(var.data$cadd.score)
has.cadd <- TRUE
max.cadd <- max(var.data$cadd.score,na.rm = TRUE)
}
# report
gsnp.data = var.data[gSNP == Linked_SNP,]
# starting <div>
cat(sprintf('<div id="variant%s">',gsnp.data$`#gSNP`))
cat(sprintf('<span class="topic">Variant ID:</span> <span class="value">%s</span><br/>', gsnp.data$gSNP))
cat(sprintf('<span class="topic">Position: </span> <span class="value">%s:%s (%s)</span><br/>', gsnp.data$Chr, gsnp.data$Pos_37, gsnp.data$Cytoband))
cat(sprintf('<span class="topic">Alleles: </span> <span class="value">%s (%s)</span><br/>', gsnp.data$`Alleles in population`, gsnp.data$`Allele frequencies`))
cat(sprintf('<span class="topic">Type: </span> <span class="value">%s</span><br/>', tools::toTitleCase(gsub(x = gsnp.data$Type,pattern = '_',replacement = ' '))))
cat(sprintf('<span class="topic">Proxy Variants: </span> <span class="value">%s </span><br/>', nrow(var.data)-1))
cat('<br/><span class="topic">Mapped genes</span>')
cat(kableExtra::kable(genes,format = 'html',col.names = NULL))
if(length(assoc) > 15 & length(assoc) %% 2 == 0)
{
assoc=cbind(assoc[1:(length(assoc)/2)],
assoc[((length(assoc)/2) +1 ):length(assoc)])
} else if (length(assoc) > 15 & length(assoc) %% 2 != 0)
{
assoc=cbind(assoc[1:(ceiling(length(assoc)/2))],
c(assoc[(ceiling((length(assoc)/2))+1):length(assoc)],''))
}
if(length(assoc)>1)
{
cat('<br/><span class="topic">Associated phenotypes</span>')
cat(kableExtra::kable(assoc,format = 'html', col.names = NULL,booktabs = TRUE) %>%
kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"),
full_width = F,
position = "left"))
}
cat('<br/>')
cat(kableExtra::kable(var.data[,.N,by=Type],format = 'html',col.names = c('type','count'),caption = '<span class="topic">Variant types</span>')%>%
kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"),
full_width = F,
position = "left") %>%
kableExtra::column_spec(1, bold = TRUE, border_right = TRUE,width="15em") %>%
kableExtra::column_spec(2, width="10em"))
cat('<br/>')
if(var.data[gSNP!=Linked_SNP & Type=='missense_variant',.N] > 0)
cat(kableExtra::kable(var.data[gSNP!=Linked_SNP & Type=='missense_variant', list(Linked_SNP,LD,Gene)],format = 'html',col.names = c('rsID','LD','Gene'),caption = '<span class="topic">Missense variants</span>')%>%
kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"),
full_width = F,
position = "left") %>%
kableExtra::column_spec(1, bold = TRUE, border_right = TRUE,width="10em") %>%
kableExtra::column_spec(2, width="10em", border_right = TRUE,extra_css = 'text-align:left;') %>%
kableExtra::column_spec(3, width="15em"))
cat('<br/>')
if(has.cadd)
cat(kableExtra::kable(head(var.data[order(cadd.score,decreasing = TRUE),
list(Linked_SNP,cadd,Deleteriousness,as.character(LD),Gene)]),
format = 'html',
col.names = c('rsID','CADD score','Deleteriousness','LD','Gene'),
caption = '<span class="topic">Most deleterious variants</span>')%>%
kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"),
full_width = F,
position = "left") %>%
kableExtra::column_spec(1, bold = TRUE, border_right = TRUE,width="10em") %>%
kableExtra::column_spec(2, width="10em", border_right = TRUE,extra_css = 'text-align:left;') %>%
kableExtra::column_spec(3, width="10em", border_right = TRUE,extra_css = 'text-align:left;') %>%
kableExtra::column_spec(4, width="10em", border_right = TRUE,extra_css = 'text-align:left;') %>%
kableExtra::column_spec(5, width="15em"))
cat('<br/>')
cat('<br/>')
if(nrow(var.data) > 1)
{
mis.var <- var.data[gSNP!=Linked_SNP & Type=='missense_variant',.N] > 0
if(has.cadd)
{
plot(
ggplot2::ggplot() +
ggplot2::geom_point(data = var.data[gSNP!=Linked_SNP & Type!='missense_variant',],mapping = aes(x=Pos_37 , y=LD,color=cadd.score),size=3) +
ggplot2::geom_point(data = var.data[gSNP!=Linked_SNP & Type=='missense_variant',],mapping = aes(x=Pos_37 , y=LD),size=3,shape=10,color='black',stroke=1.5) +
ggplot2::geom_text(data = var.data[gSNP!=Linked_SNP & Type=='missense_variant',],
mapping = aes(x=Pos_37 , y=LD,label=Linked_SNP),
hjust=-.3) +
ggplot2::geom_point(data = var.data[gSNP==Linked_SNP,],mapping = aes(x=Pos_37 , y=LD),
color='black',shape=17,size=4) +
ggplot2::labs(title = "Regional plot", x = "Position",y= expression(LD (R^2))) +
ggplot2::scale_y_continuous(limits = c(r2 ,1.035))+
ggplot2::scale_x_continuous(limits = c(gsnp.data$Pos_37-(window_size*1000) ,gsnp.data$Pos_37+(window_size*1000)))+
ggplot2::scale_color_gradient2(low = "darkblue",mid = "orange",high = "darkred",midpoint = (max.cadd/2), limits=c(0,max.cadd)) +
ggplot2::annotate(geom='text',x=gsnp.data$Pos_37,y=1.035,label=gsnp.data$gSNP) + {
if(mis.var)
ggplot2::annotate(geom='text',x=gsnp.data$Pos_37+420000,y=.98,label='missense variant')
}+{
if(mis.var)
ggplot2::geom_point(aes(x=gsnp.data$Pos_37+320000, y= 0.975),size=3,shape=10,color='black',stroke=1.5)
}+{
if(mis.var)
ggplot2::geom_rect(mapping=aes(xmin = gsnp.data$Pos_37+300000,
xmax = gsnp.data$Pos_37+500000,
ymin=.95,
ymax=1),color='black',alpha=0)
}+
ggplot2::theme_light() +
ggplot2::theme(legend.position = c(0.1,0.7))+
ggplot2::labs(color=("CADD score")))
}
else
{
plot(
ggplot2::ggplot() +
ggplot2::geom_point(data = var.data[gSNP!=Linked_SNP & Type!='missense_variant',],mapping = aes(x=Pos_37 , y=LD,color=LD),size=3) +
ggplot2::geom_point(data = var.data[gSNP!=Linked_SNP & Type=='missense_variant',],mapping = aes(x=Pos_37 , y=LD),size=3,shape=10,color='black',stroke=1.5) +
ggplot2::geom_text(data = var.data[gSNP!=Linked_SNP & Type=='missense_variant',],
mapping = aes(x=Pos_37 , y=LD,label=Linked_SNP),
hjust=-.3) +
ggplot2::geom_point(data = var.data[gSNP==Linked_SNP,],mapping = aes(x=Pos_37 , y=LD),
color='black',shape=17,size=4) +
ggplot2::labs(title = "Regional plot", x = "Position",y= expression(LD (R^2))) +
ggplot2::scale_y_continuous(limits = c(r2 ,1.035))+
ggplot2::scale_x_continuous(limits = c(gsnp.data$Pos_37-(window_size*1000) ,gsnp.data$Pos_37+(window_size*1000)))+
ggplot2::scale_color_gradient2(low = "darkblue",mid = "orange",high = "darkred",midpoint = ((1+r2)/2), limits=c(r2,1)) +
ggplot2::annotate(geom='text',x=gsnp.data$Pos_37,y=1.035,label=gsnp.data$gSNP) + {
if(mis.var)
ggplot2::annotate(geom='text',x=gsnp.data$Pos_37+420000,y=.98,label='missense variant')
}+{
if(mis.var)
ggplot2::geom_point(aes(x=gsnp.data$Pos_37+320000, y= 0.975),size=3,shape=10,color='black',stroke=1.5)
}+{
if(mis.var)
ggplot2::geom_rect(mapping=aes(xmin = gsnp.data$Pos_37+300000,
xmax = gsnp.data$Pos_37+500000,
ymin=.95,
ymax=1),color='black',alpha=0)
}+
ggplot2::theme_light() +
ggplot2::theme(legend.position = c(0.1,0.7)))
}
}
cat('</div><br/><br/><br/><hr/>')
}
vt=output[,.N-1,by=list(gSNP)]
vt[,link := sprintf('<li><a href="#variant%s">%s</a></li>', .I , gSNP)]
vt <- vt[,c(3,1)]
# cat(kableExtra::kable(vt,format = 'html',col.names = c('RSID','variants in high LD'))%>%
# kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"),
# full_width = F,
# position = "left"))
cat('<b>Search parameters:</b>\n',fill=TRUE)
cat('<b>Server:</b> ',sub(x = server,pattern = 'https?://',replacement = ''),'\n',fill=TRUE)
cat('<b>population:</b> ',db,'\n',fill=TRUE)
cat('<b>R2:</b> ',r2,'\n',fill=TRUE)
cat('<b>Window-size:</b> ',window_size,'Kb\n',fill=TRUE)
cat('<hr/>')
cat('The following variants were searched in Ensembl database.\n')
cat('<ol>')
cat(vt$link)
cat('</ol>')
cat('<hr/>')
for(i in seq_len(varCount))
{
var.data = output[`#gSNP` == i,]
makeReport_CADD(var.data)
}
cat("<b>This report was generated on: </b>",paste(Sys.time()))
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SNPannotator documentation built on Jan. 12, 2023, 5:15 p.m.
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varCount = max(output$`#gSNP`) makeReport_LD <- function(var.data) { # find unique gene names genes=var.data$Gene genes= strsplit(trimws(genes), ",\\s*") genes =unlist(genes) genes = gsub(x = genes,pattern = '(.+)(\\(.+\\))',replacement = '\\1') genes= paste(sort(unique(genes)),collapse = ', ') # associations assoc=var.data$Associations assoc= strsplit(trimws(assoc), ",\\s*") assoc =sort(unique(unlist(assoc))) # report gsnp.data = var.data[gSNP == Linked_SNP,] # starting <div> cat(sprintf('<div id="variant%s">',gsnp.data$`#gSNP`)) cat(sprintf('<span class="topic">Variant ID:</span> <span class="value">%s</span><br/>', gsnp.data$gSNP)) cat(sprintf('<span class="topic">Position: </span> <span class="value">%s:%s (%s)</span><br/>', gsnp.data$Chr, gsnp.data$Pos_37, gsnp.data$Cytoband)) cat(sprintf('<span class="topic">Alleles: </span> <span class="value">%s (%s)</span><br/>', gsnp.data$`Alleles in population`, gsnp.data$`Allele frequencies`)) cat(sprintf('<span class="topic">Type: </span> <span class="value">%s</span><br/>', tools::toTitleCase(gsub(x = gsnp.data$Type,pattern = '_',replacement = ' ')))) cat(sprintf('<span class="topic">Proxy Variants: </span> <span class="value">%s </span><br/>', nrow(var.data)-1)) cat('<br/><span class="topic">Mapped genes</span>') cat(kableExtra::kable(genes,format = 'html',col.names = NULL)) if(length(assoc) > 15 & length(assoc) %% 2 == 0) { assoc=cbind(assoc[1:(length(assoc)/2)], assoc[((length(assoc)/2) +1 ):length(assoc)]) } else if (length(assoc) > 15 & length(assoc) %% 2 != 0) { assoc=cbind(assoc[1:(ceiling(length(assoc)/2))], c(assoc[(ceiling((length(assoc)/2))+1):length(assoc)],'')) } if(length(assoc)>1) { cat('<br/><span class="topic">Associated phenotypes</span>') cat(kableExtra::kable(assoc,format = 'html', col.names = NULL,booktabs = TRUE) %>% kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = F, position = "left")) } cat('<br/>') cat(kableExtra::kable(var.data[,.N,by=Type],format = 'html',col.names = c('type','count'),caption = '<span class="topic">Variant types</span>')%>% kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = F, position = "left") %>% kableExtra::column_spec(1, bold = TRUE, border_right = TRUE,width="15em") %>% kableExtra::column_spec(2, width="10em")) cat('<br/>') cat('<br/>') if(var.data[gSNP!=Linked_SNP & Type=='missense_variant',.N] > 0) cat(kableExtra::kable(var.data[gSNP!=Linked_SNP & Type=='missense_variant', list(Linked_SNP,LD,Gene)],format = 'html',col.names = c('rsID','LD','Gene'),caption = '<span class="topic">Missense variants</span>')%>% kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = F, position = "left") %>% kableExtra::column_spec(1, bold = TRUE, border_right = TRUE,width="10em") %>% kableExtra::column_spec(2, width="10em", border_right = TRUE,extra_css = 'text-align:left;') %>% kableExtra::column_spec(3, width="15em")) cat('<br/>') cat('<br/>') if(nrow(var.data) > 1) { mis.var <- var.data[gSNP!=Linked_SNP & Type=='missense_variant',.N] > 0 plot( ggplot2::ggplot() + ggplot2::geom_point(data = var.data[gSNP!=Linked_SNP & Type!='missense_variant',],mapping = aes(x=Pos_37 , y=LD,color=LD),size=3) + ggplot2::geom_point(data = var.data[gSNP!=Linked_SNP & Type=='missense_variant',],mapping = aes(x=Pos_37 , y=LD),size=3,shape=10,color='black',stroke=1.5) + ggplot2::geom_text(data = var.data[gSNP!=Linked_SNP & Type=='missense_variant',], mapping = aes(x=Pos_37 , y=LD,label=Linked_SNP), hjust=-.3) + ggplot2::geom_point(data = var.data[gSNP==Linked_SNP,],mapping = aes(x=Pos_37 , y=LD), color='black',shape=17,size=4) + ggplot2::labs(title = "Regional plot", x = "Position",y= expression(LD (R^2))) + ggplot2::scale_y_continuous(limits = c(r2 ,1.035))+ ggplot2::scale_x_continuous(limits = c(gsnp.data$Pos_37-(window_size*1000) ,gsnp.data$Pos_37+(window_size*1000)))+ ggplot2::scale_color_gradient2(low = "darkblue",mid = "orange",high = "darkred",midpoint = ((1+r2)/2), limits=c(r2,1)) + ggplot2::annotate(geom='text',x=gsnp.data$Pos_37,y=1.035,label=gsnp.data$gSNP) + { if(mis.var) ggplot2::annotate(geom='text',x=gsnp.data$Pos_37+420000,y=.98,label='missense variant') }+{ if(mis.var) ggplot2::geom_point(aes(x=gsnp.data$Pos_37+320000, y= 0.975),size=3,shape=10,color='black',stroke=1.5) }+{ if(mis.var) ggplot2::geom_rect(mapping=aes(xmin = gsnp.data$Pos_37+300000, xmax = gsnp.data$Pos_37+500000, ymin=.95, ymax=1),color='black',alpha=0) }+ ggplot2::theme_light() + ggplot2::theme(legend.position = c(0.1,0.7))) } cat('</div><br/><br/><br/><hr/>') } makeReport_CADD <- function(var.data) { # find unique gene names genes=var.data$Gene genes= strsplit(trimws(genes), ",\\s*") genes =unlist(genes) genes = gsub(x = genes,pattern = '(.+)(\\(.+\\))',replacement = '\\1') genes= paste(sort(unique(genes)),collapse = ', ') # associations assoc=var.data$Associations assoc= strsplit(trimws(assoc), ",\\s*") assoc =sort(unique(unlist(assoc))) # check if CADD score exists and correct it has.cadd <- FALSE max.cadd <- NULL if(is.element('cadd',names(var.data))) { var.data[,cadd.score := ifelse(!grepl(x = cadd,pattern = ','), sub(x = cadd,pattern = "(.+) = (.+)",replacement = '\\2'), NA), by=Linked_SNP] var.data$cadd.score <- as.numeric(var.data$cadd.score) has.cadd <- TRUE max.cadd <- max(var.data$cadd.score,na.rm = TRUE) } # report gsnp.data = var.data[gSNP == Linked_SNP,] # starting <div> cat(sprintf('<div id="variant%s">',gsnp.data$`#gSNP`)) cat(sprintf('<span class="topic">Variant ID:</span> <span class="value">%s</span><br/>', gsnp.data$gSNP)) cat(sprintf('<span class="topic">Position: </span> <span class="value">%s:%s (%s)</span><br/>', gsnp.data$Chr, gsnp.data$Pos_37, gsnp.data$Cytoband)) cat(sprintf('<span class="topic">Alleles: </span> <span class="value">%s (%s)</span><br/>', gsnp.data$`Alleles in population`, gsnp.data$`Allele frequencies`)) cat(sprintf('<span class="topic">Type: </span> <span class="value">%s</span><br/>', tools::toTitleCase(gsub(x = gsnp.data$Type,pattern = '_',replacement = ' ')))) cat(sprintf('<span class="topic">Proxy Variants: </span> <span class="value">%s </span><br/>', nrow(var.data)-1)) cat('<br/><span class="topic">Mapped genes</span>') cat(kableExtra::kable(genes,format = 'html',col.names = NULL)) if(length(assoc) > 15 & length(assoc) %% 2 == 0) { assoc=cbind(assoc[1:(length(assoc)/2)], assoc[((length(assoc)/2) +1 ):length(assoc)]) } else if (length(assoc) > 15 & length(assoc) %% 2 != 0) { assoc=cbind(assoc[1:(ceiling(length(assoc)/2))], c(assoc[(ceiling((length(assoc)/2))+1):length(assoc)],'')) } if(length(assoc)>1) { cat('<br/><span class="topic">Associated phenotypes</span>') cat(kableExtra::kable(assoc,format = 'html', col.names = NULL,booktabs = TRUE) %>% kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = F, position = "left")) } cat('<br/>') cat(kableExtra::kable(var.data[,.N,by=Type],format = 'html',col.names = c('type','count'),caption = '<span class="topic">Variant types</span>')%>% kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = F, position = "left") %>% kableExtra::column_spec(1, bold = TRUE, border_right = TRUE,width="15em") %>% kableExtra::column_spec(2, width="10em")) cat('<br/>') if(var.data[gSNP!=Linked_SNP & Type=='missense_variant',.N] > 0) cat(kableExtra::kable(var.data[gSNP!=Linked_SNP & Type=='missense_variant', list(Linked_SNP,LD,Gene)],format = 'html',col.names = c('rsID','LD','Gene'),caption = '<span class="topic">Missense variants</span>')%>% kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = F, position = "left") %>% kableExtra::column_spec(1, bold = TRUE, border_right = TRUE,width="10em") %>% kableExtra::column_spec(2, width="10em", border_right = TRUE,extra_css = 'text-align:left;') %>% kableExtra::column_spec(3, width="15em")) cat('<br/>') if(has.cadd) cat(kableExtra::kable(head(var.data[order(cadd.score,decreasing = TRUE), list(Linked_SNP,cadd,Deleteriousness,as.character(LD),Gene)]), format = 'html', col.names = c('rsID','CADD score','Deleteriousness','LD','Gene'), caption = '<span class="topic">Most deleterious variants</span>')%>% kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = F, position = "left") %>% kableExtra::column_spec(1, bold = TRUE, border_right = TRUE,width="10em") %>% kableExtra::column_spec(2, width="10em", border_right = TRUE,extra_css = 'text-align:left;') %>% kableExtra::column_spec(3, width="10em", border_right = TRUE,extra_css = 'text-align:left;') %>% kableExtra::column_spec(4, width="10em", border_right = TRUE,extra_css = 'text-align:left;') %>% kableExtra::column_spec(5, width="15em")) cat('<br/>') cat('<br/>') if(nrow(var.data) > 1) { mis.var <- var.data[gSNP!=Linked_SNP & Type=='missense_variant',.N] > 0 if(has.cadd) { plot( ggplot2::ggplot() + ggplot2::geom_point(data = var.data[gSNP!=Linked_SNP & Type!='missense_variant',],mapping = aes(x=Pos_37 , y=LD,color=cadd.score),size=3) + ggplot2::geom_point(data = var.data[gSNP!=Linked_SNP & Type=='missense_variant',],mapping = aes(x=Pos_37 , y=LD),size=3,shape=10,color='black',stroke=1.5) + ggplot2::geom_text(data = var.data[gSNP!=Linked_SNP & Type=='missense_variant',], mapping = aes(x=Pos_37 , y=LD,label=Linked_SNP), hjust=-.3) + ggplot2::geom_point(data = var.data[gSNP==Linked_SNP,],mapping = aes(x=Pos_37 , y=LD), color='black',shape=17,size=4) + ggplot2::labs(title = "Regional plot", x = "Position",y= expression(LD (R^2))) + ggplot2::scale_y_continuous(limits = c(r2 ,1.035))+ ggplot2::scale_x_continuous(limits = c(gsnp.data$Pos_37-(window_size*1000) ,gsnp.data$Pos_37+(window_size*1000)))+ ggplot2::scale_color_gradient2(low = "darkblue",mid = "orange",high = "darkred",midpoint = (max.cadd/2), limits=c(0,max.cadd)) + ggplot2::annotate(geom='text',x=gsnp.data$Pos_37,y=1.035,label=gsnp.data$gSNP) + { if(mis.var) ggplot2::annotate(geom='text',x=gsnp.data$Pos_37+420000,y=.98,label='missense variant') }+{ if(mis.var) ggplot2::geom_point(aes(x=gsnp.data$Pos_37+320000, y= 0.975),size=3,shape=10,color='black',stroke=1.5) }+{ if(mis.var) ggplot2::geom_rect(mapping=aes(xmin = gsnp.data$Pos_37+300000, xmax = gsnp.data$Pos_37+500000, ymin=.95, ymax=1),color='black',alpha=0) }+ ggplot2::theme_light() + ggplot2::theme(legend.position = c(0.1,0.7))+ ggplot2::labs(color=("CADD score"))) } else { plot( ggplot2::ggplot() + ggplot2::geom_point(data = var.data[gSNP!=Linked_SNP & Type!='missense_variant',],mapping = aes(x=Pos_37 , y=LD,color=LD),size=3) + ggplot2::geom_point(data = var.data[gSNP!=Linked_SNP & Type=='missense_variant',],mapping = aes(x=Pos_37 , y=LD),size=3,shape=10,color='black',stroke=1.5) + ggplot2::geom_text(data = var.data[gSNP!=Linked_SNP & Type=='missense_variant',], mapping = aes(x=Pos_37 , y=LD,label=Linked_SNP), hjust=-.3) + ggplot2::geom_point(data = var.data[gSNP==Linked_SNP,],mapping = aes(x=Pos_37 , y=LD), color='black',shape=17,size=4) + ggplot2::labs(title = "Regional plot", x = "Position",y= expression(LD (R^2))) + ggplot2::scale_y_continuous(limits = c(r2 ,1.035))+ ggplot2::scale_x_continuous(limits = c(gsnp.data$Pos_37-(window_size*1000) ,gsnp.data$Pos_37+(window_size*1000)))+ ggplot2::scale_color_gradient2(low = "darkblue",mid = "orange",high = "darkred",midpoint = ((1+r2)/2), limits=c(r2,1)) + ggplot2::annotate(geom='text',x=gsnp.data$Pos_37,y=1.035,label=gsnp.data$gSNP) + { if(mis.var) ggplot2::annotate(geom='text',x=gsnp.data$Pos_37+420000,y=.98,label='missense variant') }+{ if(mis.var) ggplot2::geom_point(aes(x=gsnp.data$Pos_37+320000, y= 0.975),size=3,shape=10,color='black',stroke=1.5) }+{ if(mis.var) ggplot2::geom_rect(mapping=aes(xmin = gsnp.data$Pos_37+300000, xmax = gsnp.data$Pos_37+500000, ymin=.95, ymax=1),color='black',alpha=0) }+ ggplot2::theme_light() + ggplot2::theme(legend.position = c(0.1,0.7))) } } cat('</div><br/><br/><br/><hr/>') } vt=output[,.N-1,by=list(gSNP)] vt[,link := sprintf('<li><a href="#variant%s">%s</a></li>', .I , gSNP)] vt <- vt[,c(3,1)] # cat(kableExtra::kable(vt,format = 'html',col.names = c('RSID','variants in high LD'))%>% # kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), # full_width = F, # position = "left")) cat('<b>Search parameters:</b>\n',fill=TRUE) cat('<b>Server:</b> ',sub(x = server,pattern = 'https?://',replacement = ''),'\n',fill=TRUE) cat('<b>population:</b> ',db,'\n',fill=TRUE) cat('<b>R2:</b> ',r2,'\n',fill=TRUE) cat('<b>Window-size:</b> ',window_size,'Kb\n',fill=TRUE) cat('<hr/>') cat('The following variants were searched in Ensembl database.\n') cat('<ol>') cat(vt$link) cat('</ol>') cat('<hr/>') for(i in seq_len(varCount)) { var.data = output[`#gSNP` == i,] makeReport_CADD(var.data) } cat("<b>This report was generated on: </b>",paste(Sys.time()))
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