Rfastp 1.0.0
The Rfastp package provides an interface to the all-in-one preprocessing for FastQ files toolkit fastp(Chen et al. 2018).
Use the BiocManager
package to download and install the package from
Bioconductor as follows:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("Rfastp")
If required, the latest development version of the package can also be installed from GitHub.
BiocManager::install("remotes")
BiocManager::install("RockefellerUniversity/Rfastp")
Once the package is installed, load it into your R session:
library(Rfastp)
The package contains three example fastq files, corresponding to a single-end fastq file, a pair of paired-end fastq files.
se_read1 <- system.file("extdata","Fox3_Std_small.fq.gz",package="Rfastp")
pe_read1 <- system.file("extdata","reads1.fastq.gz",package="Rfastp")
pe_read2 <- system.file("extdata","reads2.fastq.gz",package="Rfastp")
outputPrefix <- tempfile(tmpdir = tempdir())
Rfastp support multiple threads, set threads number by parameter thread
.
se_json_report <- rfastp(read1 = se_read1,
outputFastq = paste0(outputPrefix, "_se"), thread = 4)
pe_json_report <- rfastp(read1 = pe_read1, read2 = pe_read2,
outputFastq = paste0(outputPrefix, "_pe"))
pe_merge_json_report <- rfastp(read1 = pe_read1, read2 = pe_read2, merge = TRUE,
outputFastq = paste0(outputPrefix, '_unpaired'),
mergeOut = paste0(outputPrefix, "_merged.fastq.gz"))
umi_json_report <- rfastp(read1 = pe_read1, read2 = pe_read2,
outputFastq = paste0(outputPrefix, '_umi1'), umi = TRUE, umiLoc = "read1",
umiLength = 16)
the following example will add prefix string before the UMI sequence in the sequence name. An “_" will be added between the prefix string and UMI sequence. The UMI sequences will be inserted into the sequence name before the first space.
umi_json_report <- rfastp(read1 = pe_read1, read2 = pe_read2,
outputFastq = paste0(outputPrefix, '_umi2'), umi = TRUE, umiLoc = "read1",
umiLength = 16, umiPrefix = "#", umiNoConnection = TRUE,
umiIgnoreSeqNameSpace = TRUE)
Trim poor quality bases at 3’ end base by base with quality higher than 5; trim poor quality bases at 5’ end by a 29bp window with mean quality higher than 20; disable the polyG trimming, specify the adapter sequence for read1.
clipr_json_report <- rfastp(read1 = se_read1,
outputFastq = paste0(outputPrefix, '_clipr'),
disableTrimPolyG = TRUE,
cutLowQualFront = TRUE,
cutFrontWindowSize = 29,
cutFrontMeanQual = 20,
cutLowQualTail = TRUE,
cutTailWindowSize = 1,
cutTailMeanQual = 5,
minReadLength = 29,
adapterSequenceRead1 = 'GTGTCAGTCACTTCCAGCGG'
)
rfastq can accept multiple input files, and it will concatenate the input files into one and the run fastp.
pe001_read1 <- system.file("extdata","splited_001_R1.fastq.gz",
package="Rfastp")
pe002_read1 <- system.file("extdata","splited_002_R1.fastq.gz",
package="Rfastp")
pe003_read1 <- system.file("extdata","splited_003_R1.fastq.gz",
package="Rfastp")
pe004_read1 <- system.file("extdata","splited_004_R1.fastq.gz",
package="Rfastp")
inputfiles <- c(pe001_read1, pe002_read1, pe003_read1, pe004_read1)
cat_rjson_report <- rfastp(read1 = inputfiles,
outputFastq = paste0(outputPrefix, "_merged1"))
pe001_read2 <- system.file("extdata","splited_001_R2.fastq.gz",
package="Rfastp")
pe002_read2 <- system.file("extdata","splited_002_R2.fastq.gz",
package="Rfastp")
pe003_read2 <- system.file("extdata","splited_003_R2.fastq.gz",
package="Rfastp")
pe004_read2 <- system.file("extdata","splited_004_R2.fastq.gz",
package="Rfastp")
inputR2files <- c(pe001_read2, pe002_read2, pe003_read2, pe004_read2)
catfastq(output = paste0(outputPrefix,"_merged2_R2.fastq.gz"),
inputFiles = inputR2files)
dfsummary <- qcSummary(pe_json_report)
p1 <- curvePlot(se_json_report)
p1
p2 <- curvePlot(se_json_report, curve="content_curves")
p2