我正在尝试生成一个质量控制报告，该报告在多个文件夹（每个文件夹对应于一个实验）上循环（应用），并为每个加载结果创建表格和绘图（在函数内）。生成的 pdf 应包含文件夹的名称，后跟按顺序排列的表格和绘图。我首先创建了 R 脚本（运行良好），然后创建了一个 rnw 文件。图确实生成了，但存在 2 个问题（pdf outout）：
-
在块loop_n_plots中不生成表;
-
创建所有绘图后，会出现一条意外的混乱线，看起来像列表的输出。
问：如何获取 pdf 中的表格？在块"table_files"中生成的表有效，但应用函数中的表不起作用。为什么？更一般地说，我正在尝试做的事情（amd 我怎么做）对于 knitr 报告可以吗？最好在列表中添加表和绘图，然后循环列表以打印它们吗？
我已经使用块设置玩了一段时间，但没有任何效果。
示例代码：
documentclass{report}
begin{document}
title{Sequencing Quality Report}
author{Deep Sequencing Group - SFB655}
maketitle
<<knitr_option, cache=FALSE, echo=FALSE, results='hide'>>=
library(knitr)
## set global chunk options
opts_chunk$set(fig.align='center', fig.width=14, fig.heigth=8, out.width="1.2\textwidth", par=TRUE)
@
<<R_arguments, cache=FALSE, echo=FALSE, include=FALSE>>=
###### Libraries ######
library(reshape)
library(ggplot2)
theme_set(theme_bw(16)) # removes grey grid and increases letter size. Ideal for presentations
library(RColorBrewer)
library(plyr)
library(scales) # for natural numbers in axis
library(xtable)
library(rattle) # needed to generate a table in knitr?
#######################
###### Function definitions ######
## ggplot theme with extra space between legends and axis
gg.axis.space <- theme(axis.title.y=element_text(vjust=0.2), axis.title.x=element_text(vjust=0.2))
ReturnStatsPlotsAndTables <- function(fqc.folder){
# for(fqc.folder in fq_fastqc.folders){
######################################
## for each folder in the vector will
## plot stats and
## print tables of fastQC results
## which library is being analysed?
fastq.lib <- data.frame(Libraries = gsub(".*/(L.*)\.fq_fastqc", "\1", fqc.folder, perl=T))
xtable(fastq.lib)
## Basic statistics - table ##
stats.path <- paste(fqc.folder, "/", "Basic_Statistics_fastqc_data.temp", sep="")
basic.stats <- read.table(stats.path, header = TRUE, sep = "t", stringsAsFactors = FALSE)
# basic.stats[ ,1:2]
xtable(basic.stats[ ,1:2])
## Summary of filters - table ##
stats.path <- paste(fqc.folder, "/", "filters_summary_fastqc_data.temp", sep="")
summary.filters <- read.table(stats.path,
header = TRUE, sep = "t", stringsAsFactors = FALSE)
# summary.filters
xtable(summary.filters)
## Per base sequence quality ##
stats.path <- paste(fqc.folder, "/", "Per_base_sequence_quality_fastqc_data.temp", sep="")
base.qual <- read.table(stats.path,
header = TRUE, sep = "t", stringsAsFactors = FALSE)
base.qual$Base <- factor(base.qual$Base, as.character(base.qual$Base)) # re-order the levels by order of appearance in DF
plot.new()
base.qual.p <- ggplot(base.qual, aes(x = Base, ymin = X10th.Percentile, lower = Lower.Quartile, middle = Median, upper = Upper.Quartile, ymax = X90th.Percentile, fill = Lower.Quartile)) + geom_boxplot(stat = "identity") +
theme(axis.text.x = element_text(angle=30, hjust=1, vjust=1)) +
annotate("rect", xmin=-Inf, xmax=Inf, ymin=0, ymax=20, alpha=0.1, fill="red") +
annotate("rect", xmin=-Inf, xmax=Inf, ymin=20, ymax=28, alpha=0.1, fill="yellow") +
annotate("rect", xmin=-Inf, xmax=Inf, ymin=28, ymax=Inf, alpha=0.1, fill="green") +
ggtitle("Per base sequence quality") + ylab("Quality score (Phred score) ") + xlab("Position of base in read")
print(base.qual.p)
}
@
chapter{Preamble}
This an automated quality control report generated for the following fastq files:
<<table_files, echo=FALSE, results="asis">>=
##############################################
## loop over fastQC folder and parse txt files:
## list and read fastqc_data.temp old files
# testing #
# setwd("/projects/seq-work/analysis/martinad/p0196-totalRNA/")
folder <- "./"
filenames <- list.files(path=folder, pattern="fastqc_data.temp", recursive=TRUE)
fq_fastqc.folders <- unique(dirname(filenames)) # the folders that contain fastQC
fastq.libs <- data.frame(Libraries = gsub(".*/(L.*)\.fq_fastqc", "\1", fq_fastqc.folders, perl=T))
xtable(fastq.libs)
@
chapter{FastQC}
<<loop_n_plots, echo=FALSE, results='asis'>>=
## do the plotting
sapply(fq_fastqc.folders[1:3], ReturnStatsPlotsAndTables)
@
end{document}
函数 ReturnStatsPlotsAndTables 实际上更长，这足以让人了解正在发生的事情。
找到了包含 2 个步骤的解决方案：
-
将 sapply 替换为包含函数 ReturnStatsPlotsAndTables 指令的 for 循环;
-
在 for 循环中，需要使用以下命令显式打印表：
print（xtable（fastq.lib））
这是最终代码：
documentclass{report}
begin{document}
title{Sequencing Quality Report}
author{Deep Sequencing Group - SFB655}
maketitle
<<knitr_option, cache=FALSE, echo=FALSE, results='hide'>>=
library(knitr)
## set global chunk options
opts_chunk$set(fig.align='center', fig.width=14, fig.heigth=8, out.width="1.2\textwidth", par=TRUE)
@
<<R_arguments, cache=FALSE, echo=FALSE, include=FALSE>>=
###### Libraries ######
library(reshape)
library(ggplot2)
theme_set(theme_bw(16)) # removes grey grid and increases letter size. Ideal for presentations
library(RColorBrewer)
library(plyr)
library(scales) # for natural numbers in axis
library(xtable)
library(rattle) # needed to generate a table in knitr?
#######################
###### Function definitions ######
## ggplot theme with extra space between legends and axis
gg.axis.space <- theme(axis.title.y=element_text(vjust=0.2), axis.title.x=element_text(vjust=0.2))
@
chapter{Preamble}
This an automated quality control report generated for the following fastq files:
<<table_files, echo=FALSE, results="asis">>=
##############################################
## loop over fastQC folder and parse txt files:
## list and read fastqc_data.temp old files
# testing #
# setwd("/projects/seq-work/analysis/martinad/p0196-totalRNA/")
folder <- "./"
filenames <- list.files(path=folder, pattern="fastqc_data.temp", recursive=TRUE)
fq_fastqc.folders <- unique(dirname(filenames)) # the folders that contain fastQC
fastq.libs <- data.frame(Libraries = gsub(".*/(L.*)\.fq_fastqc", "\1", fq_fastqc.folders, perl=T))
xtable(fastq.libs)
@
chapter{FastQC}
<<loop_n_plots, echo=FALSE, results="asis">>=
## do the plotting
# sapply(fq_fastqc.folders[1:3], ReturnStatsPlotsAndTables)
for (fqc.folder in fq_fastqc.folders[1:2]){
# for(fqc.folder in fq_fastqc.folders){
######################################
## for each folder in the vector will
## plot stats and
## print tables of fastQC results
# print(fqc.folder)
## which library is being analysed?
fastq.lib <- data.frame(Libraries = gsub(".*/(L.*)\.fq_fastqc", "\1", fqc.folder, perl=T))
print(xtable(fastq.lib))
## Basic statistics - table ##
stats.path <- paste(fqc.folder, "/", "Basic_Statistics_fastqc_data.temp", sep="")
basic.stats <- read.table(stats.path, header = TRUE, sep = "t", stringsAsFactors = FALSE)
# basic.stats[ ,1:2]
print(xtable(basic.stats[ ,1:2]))
## Summary of filters - table ##
stats.path <- paste(fqc.folder, "/", "filters_summary_fastqc_data.temp", sep="")
summary.filters <- read.table(stats.path,
header = TRUE, sep = "t", stringsAsFactors = FALSE)
# summary.filters
print(xtable(summary.filters))
## Per base sequence quality ##
stats.path <- paste(fqc.folder, "/", "Per_base_sequence_quality_fastqc_data.temp", sep="")
base.qual <- read.table(stats.path,
header = TRUE, sep = "t", stringsAsFactors = FALSE)
base.qual$Base <- factor(base.qual$Base, as.character(base.qual$Base)) # re-order the levels by order of appearance in DF
plot.new()
base.qual.p <- ggplot(base.qual, aes(x = Base, ymin = X10th.Percentile, lower = Lower.Quartile, middle = Median, upper = Upper.Quartile, ymax = X90th.Percentile, fill = Lower.Quartile)) + geom_boxplot(stat = "identity") +
theme(axis.text.x = element_text(angle=30, hjust=1, vjust=1)) +
annotate("rect", xmin=-Inf, xmax=Inf, ymin=0, ymax=20, alpha=0.1, fill="red") +
annotate("rect", xmin=-Inf, xmax=Inf, ymin=20, ymax=28, alpha=0.1, fill="yellow") +
annotate("rect", xmin=-Inf, xmax=Inf, ymin=28, ymax=Inf, alpha=0.1, fill="green") +
ggtitle("Per base sequence quality") + ylab("Quality score (Phred score) ") + xlab("Position of base in read")
print(base.qual.p)
}
@
end{document}