For this set of exercises, we will use the chip_1_1.fq.bz2
and chip_2_1.fq.bz2
files from the QuasR
package. You can reach the folder that contains the files as follows:
folder=(system.file(package="QuasR", "extdata"))
dir(folder) # will show the contents of the folder
- Plot the base quality distributions of the ChIP-seq samples
Rqc
package. HINT: You need to provide a regular expression pattern for extracting the right files from the folder."^chip"
matches the files beginning with "chip". [Difficulty: Beginner/Intermediate]
solution:
folder=(system.file(package="QuasR", "extdata"))
library(Rqc)
folder = system.file(package="ShortRead", "extdata/E-MTAB-1147")
# feeds fastq.qz files in "folder" to quality check function
qcRes=rqc(path = folder, pattern = "^chip", openBrowser=FALSE)
rqcCycleQualityBoxPlot(qcRes)
- Now we will trim the reads based on the quality scores. Let's trim 2-4 bases on the 3' end depending on the quality scores. You can use the
QuasR::preprocessReads()
function for this purpose. [Difficulty: Beginner/Intermediate]
solution:
#coming soon
- Align the trimmed and untrimmed reads using
QuasR
and plot alignment statistics, did the trimming improve alignments? [Difficulty: Intermediate/Advanced]
solution:
#coming soon