整理转录组测序原始和比对数据的质量控制参数结果,并实现可视化展示。
安装R包:
# install.packages("devtools")
devtools::install_github("lizhihui1996/RawdataQC")
加载R包:
library(RawdataQC)
#> Loading required package: gridExtra
#> Loading required package: data.table
#> Loading required package: ggsci
#> Loading required package: ggthemes
#> Loading required package: ggplot2
## basic example code
summary(QC)
#> library batch total_reads gc_content
#> Length:180 Length:180 Min. :31364100 Min. :44.00
#> Class :character Class :character 1st Qu.:36292119 1st Qu.:46.00
#> Mode :character Mode :character Median :39587210 Median :47.00
#> Mean :40533170 Mean :46.87
#> 3rd Qu.:43738466 3rd Qu.:48.00
#> Max. :56719228 Max. :50.00
#> q30_rate human_rate rRNA_rate contamination_rate
#> Min. :0.9186 Min. :97.86 Min. :0.00000 Min. :0.2700
#> 1st Qu.:0.9438 1st Qu.:98.48 1st Qu.:0.01000 1st Qu.:0.3500
#> Median :0.9461 Median :98.74 Median :0.03500 Median :0.4025
#> Mean :0.9457 Mean :98.67 Mean :0.07522 Mean :0.5122
#> 3rd Qu.:0.9484 3rd Qu.:98.86 3rd Qu.:0.12625 3rd Qu.:0.6250
#> Max. :0.9535 Max. :99.19 Max. :0.47500 Max. :1.1300
#> error_rate bias insertsize exonic
#> Min. :0.00000 Min. :0.910 Min. :263.0 Min. :0.3959
#> 1st Qu.:0.01000 1st Qu.:0.980 1st Qu.:284.8 1st Qu.:0.4293
#> Median :0.01000 Median :1.010 Median :290.0 Median :0.4456
#> Mean :0.01006 Mean :1.009 Mean :290.8 Mean :0.4446
#> 3rd Qu.:0.01000 3rd Qu.:1.030 3rd Qu.:297.0 3rd Qu.:0.4602
#> Max. :0.02000 Max. :1.130 Max. :314.0 Max. :0.4944
#> intronic intergenic type
#> Min. :0.4550 Min. :0.04404 Length:180
#> 1st Qu.:0.4843 1st Qu.:0.05073 Class :character
#> Median :0.4982 Median :0.05410 Mode :character
#> Mean :0.5012 Mean :0.05427
#> 3rd Qu.:0.5171 3rd Qu.:0.05672
#> Max. :0.5503 Max. :0.06865
结果示例:
#> TableGrob (2 x 1) "arrange": 2 grobs
#> z cells name grob
#> 1 1 (1-1,1-1) arrange gtable[layout]
#> 2 2 (2-2,1-1) arrange gtable[colhead-fg]
#> Number of passed samples Number of failed samples Number of total samples
#> 1 177 3 180
#> Ratio of passed samples
#> 1 0.98
#> library exonic intronic intergenic
#> 1 X1_10_d_2 0.396 0.550 0.054
#> 2 X1_16_d_3 0.398 0.548 0.054
#> 3 X2_16_d_3 0.400 0.550 0.050
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