htmltools::img(src = knitr::image_uri(system.file("extdata", "DNA.png", package = "GWASinspector")), alt = 'logo', style = 'position:absolute; top:0; right:20%; padding:10px;')
Start Time: r format(.QC$config$new_items$starttime, "%b %d %Y - %X")
End time: r format(.QC$config$new_items$endtime, "%b %d %Y - %X")
Script version: r .QC$script.version
System Information : r .QC$r.version
`r report.table <- data.table(sapply(.QC$qc.study.list, function(x) return(paste0("",basename(x$file.path),""))))
report.table <- cbind(sapply(.QC$qc.study.list, function(x) return(x$number)) , report.table) colnames(report.table) <- c('File number', 'Input file name') row.names(report.table) <- sapply(.QC$qc.study.list, function(x) return(x$number))
kable(report.table, align = "c" ,escape = FALSE, format = "html") %>% kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = FALSE, position = "left") %>% kableExtra::column_spec(1, bold = TRUE,width="10em",extra_css='text-align:center', border_right = T) %>% kableExtra::column_spec(2, extra_css='text-align:left') `
`r report.table <- t(data.table( "Sample size (Max)" = sapply(.QC$qc.study.list, function(x) return(thousand_sep(x$MAX_N_TOTAL))),
"<span class='mainItem'>Missing columns</span>" = sapply(.QC$qc.study.list, function(x) return(paste(x$missing.Columns, collapse = ' | '))), "<span class='mainItem'>Variants in input file</span>" = sapply(.QC$qc.study.list, function(x) return(thousand_sep(x$input.data.rowcount))), "<span class='item'>Missing crucial variable</span>" = sapply(.QC$qc.study.list, function(x) return(calculatePercent(x$missing.crucial.rowcount, x$input.data.rowcount, pretty = T))), "<span class='mainItem'>Variant count after step 1</span>" = sapply(.QC$qc.study.list, function(x) return(calculatePercent(x$rowcount.step1, x$input.data.rowcount, decimal.place=3, pretty = T))), "<span class='item'>Monomorphic variants</span>" = sapply(.QC$qc.study.list, function(x) return(calculatePercent(x$monomorphic.count,x$rowcount.step3,pretty=TRUE))), "<span class='mainItem'>Variant count after step 2</span>" = sapply(.QC$qc.study.list, function(x) return(calculatePercent(x$rowcount.step2, x$input.data.rowcount, decimal.place=3, pretty = T))), "<span class='mainItem'>Variant count after step 3</span>" = sapply(.QC$qc.study.list, function(x) return(calculatePercent(x$rowcount.step3, x$input.data.rowcount, decimal.place=4, pretty = T))), "<span class='mainItem'>SNP variants</span>" = sapply(.QC$qc.study.list, function(x) return(calculatePercent(sum(as.numeric(gsub(x=x$tables$multi_allele_count_preProcess[1:3], pattern = ",", replacement = ""))), x$rowcount.step3, decimal.place=4, pretty = T))), "<span class='mainItem'>Non-SNP variants</span>" = sapply(.QC$qc.study.list, function(x) return(calculatePercent(sum(as.numeric(gsub(x=x$tables$multi_allele_count_preProcess[4:6], pattern = ",", replacement = ""))), x$rowcount.step3, decimal.place=4, pretty = T))), "<span class='mainItem'>Palindromic variants</span>" = sapply(.QC$qc.study.list, function(x) return(calculatePercent(x$palindromic.rows,x$rowcount.step3,pretty=TRUE))), "<span class='mainItem'>Genotyped variants</span>" = sapply(.QC$qc.study.list, function(x) return(ifelse(x$tables$imputed.tbl[IMPUTED=='genotyped',.N] == 0, "NA", calculatePercent(as.numeric(x$tables$imputed.tbl[IMPUTED=="genotyped",N]),x$rowcount.step3,pretty=TRUE)))), "<span class='mainItem'>Imputed variants</span>" = sapply(.QC$qc.study.list, function(x) return(ifelse(x$tables$imputed.tbl[IMPUTED=='imputed',.N] == 0, "NA", calculatePercent(as.numeric(x$tables$imputed.tbl[IMPUTED=="imputed",N]),x$rowcount.step3,pretty=TRUE)))), "<span class='mainItem'>Negative-strand variants</span>" = sapply(.QC$qc.study.list, function(x) return(calculatePercent(x$neg.strand.count,x$rowcount.step3,pretty=TRUE))), "<span class='mainItem'>Allele frequency correlation</span>" = '', "<span class='item'>Standard reference</span>" = sapply(.QC$qc.study.list, function(x) return(x$AFcor.std_ref)), "<span class='item'>Alternative reference</span>" = sapply(.QC$qc.study.list, function(x) return(x$AFcor.alt_ref)), "<span class='mainItem'>Palindromic allele frequency correlation</span>" = '', "<span class='item'>Standard reference</span>" = sapply(.QC$qc.study.list, function(x) return(x$AFcor.palindromic.std_ref)), "<span class='item'>Alternative reference</span>" = sapply(.QC$qc.study.list, function(x) return(x$AFcor.palindromic.alt_ref)), "<span class='mainItem'>Lambda - total</span>" = sapply(.QC$qc.study.list, function(x) return(x$lambda)), "<span class='mainItem'>Lambda - genotyped</span>" = sapply(.QC$qc.study.list, function(x) return(x$lambda.gen)), "<span class='mainItem'>Lambda - imputed</span>" = sapply(.QC$qc.study.list, function(x) return(x$lambda.imp)), "<span class='mainItem'>P-value correlation (obs. vs exp.)</span>" = sapply(.QC$qc.study.list, function(x) return(x$PVcor)), "<span class='mainItem'>Visscher's statistic (HQ variants)</span>" = sapply(.QC$qc.study.list, function(x) return(x$Visschers.stat.HQ)), "<span class='mainItem'>Fixed HWE P-value</span>" = sapply(.QC$qc.study.list, function(x) return(x$fixed.hwep)), "<span class='mainItem'>Fixed imputation quality</span>" = sapply(.QC$qc.study.list, function(x) return(x$fixed.impq)), "<span class='mainItem'>Fixed sample size</span>" = sapply(.QC$qc.study.list, function(x) return(x$fixed.n_total)), "<span class='mainItem'>Fixed call rate</span>" = sapply(.QC$qc.study.list, function(x) return(x$fixed.callrate)), "<span class='mainItem'>Effect size</span>" = ' ', "<span class='item'>Min.</span>" = sapply(.QC$qc.study.list, function(x) return(x$tables$variable.summary['Min.', .QC$config$input_parameters$effect_type_string])), "<span class='item'>1st Qu.</span>" = sapply(.QC$qc.study.list, function(x) return(x$tables$variable.summary['1st Qu.', .QC$config$input_parameters$effect_type_string])), "<span class='item'>Median</span>" = sapply(.QC$qc.study.list, function(x) return(x$tables$variable.summary['Median', .QC$config$input_parameters$effect_type_string])), "<span class='item'>Mean</span>" = sapply(.QC$qc.study.list, function(x) return(x$tables$variable.summary['Mean', .QC$config$input_parameters$effect_type_string])), "<span class='item'>3rd Qu.</span>" = sapply(.QC$qc.study.list, function(x) return(x$tables$variable.summary['3rd Qu.', .QC$config$input_parameters$effect_type_string])), "<span class='item'>Max.</span>" = sapply(.QC$qc.study.list, function(x) return(x$tables$variable.summary['Max.', .QC$config$input_parameters$effect_type_string])), "<span class='item'>Min. (HQ variants)</span>" = sapply(.QC$qc.study.list, function(x) return(ifelse(nrow(x$tables$variable.summary.HQ) > 0, x$tables$variable.summary.HQ['Min.', .QC$config$input_parameters$effect_type_string], NA))), "<span class='item'>Max. (HQ variants)</span>" = sapply(.QC$qc.study.list, function(x) return(ifelse(nrow(x$tables$variable.summary.HQ) > 0, x$tables$variable.summary.HQ['Max.', .QC$config$input_parameters$effect_type_string], NA))), "<span class='mainItem'>Standard error (median)</span>" = sapply(.QC$qc.study.list, function(x) return(x$tables$variable.summary['Median','STDERR'])), "<span class='mainItem'>Standard error (median) (HQ variants)</span>" = sapply(.QC$qc.study.list, function(x) return(ifelse(nrow(x$tables$variable.summary.HQ) > 0, x$tables$variable.summary.HQ['Median','STDERR'], NA))) )) colnames(report.table) <- sapply(.QC$qc.study.list, function(x) return(x$number)) study.col.count <- length(.QC$qc.study.list) + 1
prc <- sprintf("%s%%", study.col.count * 15)
kable(report.table,escape = FALSE, align = "c" , format = "html") %>% kableExtra::kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = TRUE, position = "left") %>% kableExtra::column_spec(1, bold = TRUE, width="20em", border_right = T,extra_css="vertical-align:middle" ) %>% kableExtra::column_spec(2:study.col.count, width="20em" , border_right = T ) %>% kableExtra::scroll_box(width = prc)
`
`r if(file.exists(.QC$config$paths$precisionPlotPath) & .QC$graphic.device != 'tiff') htmltools::img(src = knitr::image_uri(.QC$config$paths$precisionPlotPath), alt = 'MAF',width='80%')
`
`r if(file.exists(.QC$config$paths$skew_kurt) & .QC$graphic.device != 'tiff') htmltools::img(src = knitr::image_uri(.QC$config$paths$skew_kurt), alt = 'MAF',width='80%')
`
r paste0("<a target='_blank' href='",basename(.QC$config$paths$effsizePlotPath),"'><font color='blue'>click for full-size plot</font></a>")
`r if(file.exists(.QC$config$paths$effsizePlotPath) & .QC$graphic.device != 'tiff' ) htmltools::img(src = knitr::image_uri(.QC$config$paths$effsizePlotPath), alt = 'MAF',height='100%')
`
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