In bakerwm/goldclipReport: Reporter for GoldCLIP (Title Case)

#Knitr settings
knitr::opts_chunk$set(
  warning=FALSE, message=FALSE, echo=TRUE, tidy=FALSE, error=FALSE,
  fig.show='hold', fig.width=3.5, fig.height = 3.5
)
options(width=150)

if(is.null(experiment)) experiment <- "Sequencing data"

• Date: r Sys.Date()
• Scanned QC directory (qc.path): r qc.path
• R packages: Report generated with the R package fastqcr version r packageDescription("fastqcr")$Version
• Experiment description: r experiment

Required R packages

library(goldclipData)
library(fastqcr)
library(dplyr)
library(ggplot2)
library(cowplot)

Aggregating Reports

qc <- qc_aggregate(qc.path, progressbar = FALSE)
#qc

General statistics

qcgs <- qc_stats(qc)
qcgs <- mutate(qcgs, tot.seq = prettyNum(tot.seq, big.mark = ",", scientific = FALSE),
               pct.dup = paste0(pct.dup, '%'),
               pct.gc  = paste0(pct.gc, '%'))
names(qcgs) <- c('Sample', 'Duplication', 'GC', 'Total_sequences', 'Length (nt)')
qcgs

Column names:

• Sample: sample names
• Duplication: percentage of duplicate reads
• GC Percentage: percentage of GC content
• Total_sequences: total sequences (i.e.: the number of reads)
• Length: sequence length

```{block, type = "block"} The table shows, for each sample, some general statistics such as the total number of reads, the length of reads, the percentage of GC content and the percentage of duplicate reads

## Summary

```r
summary(qc)

Column names:

• module: fastqc modules
• nb_samples: the number of samples tested
• nb_pass, nb_fail, nb_warn: the number of samples that passed, failed and warned, respectively.
• failed, warned: the name of samples that failed and warned, respectively.

```{block, type = "block"} The table shows, for each FastQC module, the number and the name of samples that failed or warned.

## Inspecting Problems

### Failed modules in the most samples


```r
qc_fails(qc, "module")

```{block, type = "block"} For each module, the number of problems (failures) and the name of samples, that failed, are shown.

### Warned module in the most samples


```r
qc_warns(qc, "module")

Samples with Problems

• Compact format

qc_problems(qc, "sample")

Inspecting base quality for each sample

# 1. base quality
# 2. sequence content
qc.file <- fastqcFiles(qc.path)
temp <- lapply(qc.file, function(f) {
  p <- fastqcPlot(f)
  print(p)
})

bakerwm/goldclipReport documentation built on July 9, 2019, 4:54 p.m.