Reads Manipulation

fastp
Function: An ultra-fast all-in-one FASTQ preprocessor
Usage: fastp [options] -i <file> -o <file>
Supported input format: FASTQ
multiBamSummary
Function: This tool generates a matrix of read coverages for a list of genomic regions and at least two samples (BAM files). The genome is split into bins of the given size. For each bin, the number of reads found in each BAM file is counted. Alternatively, an interval file with pre-defined genomic regions can be provided.
Usage: multiBamSummary BED-file --BED selection.bed --bamfiles file1.bam file2.bam -out results.npz
Cutadapt
Function: Trim a 3’ adapter by using cutadapt
Usage: cutadapt -a AACCGGTT -o output.fastq input.fastq
bowtie-build
Function: bowtie-build builds a Bowtie index from a set of DNA sequences. bowtie-build outputs a set of 6 files with suffixes .1.ebwt, .2.ebwt, .3.ebwt, .4.ebwt, .rev.1.ebwt, and .rev.2.ebwt. (If the total length of all the input sequences is greater than about 4 billion, then the index files will end in ebwtl instead of ebwt.) These files together constitute the index: they are all that is needed to align reads to that reference. The original sequence files are no longer used by Bowtie once the index is built.
Usage: bowtie-build [options]* <reference_in> <ebwt_base>
multiBamSummary
Function: This tool generates a matrix of read coverages for a list of genomic regions and at least two samples (BAM files). The genome is split into bins of the given size. For each bin, the number of reads found in each BAM file is counted. Alternatively, an interval file with pre-defined genomic regions can be provided.
Usage: multiBamSummary bins --bamfiles file1.bam file2.bam -out results.npz
sickle
Function: Sickle is a tool that uses sliding windows along with quality and length thresholds to determine when quality is sufficiently low to trim the 3'-end of reads and also determines when the quality is sufficiently high enough to trim the 5'-end of reads. It will also discard reads based upon the length threshold. It takes the quality values and slides a window across them whose length is 0.1 times the length of the read. If this length is less than 1, then the window is set to be equal to the length of the read. Otherwise, the window slides along the quality values until the average quality in the window rises above the threshold, at which point the algorithm determines where within the window the rise occurs and cuts the read and quality there for the 5'-end cut. Then when the average quality in the window drops below the threshold, the algorithm determines where in the window the drop occurs and cuts both the read and quality strings there for the 3'-end cut. However, if the length of the remaining sequence is less than the minimum length threshold, then the read is discarded entirely (or replaced with an "N" record). 5'-end trimming can be disabled.
Usage: sickle se -t [solexa|illumina|sanger] -f input_reads.fastq -o output_reads_trimmed.fastq
samtools rmdup
Function: Remove potential PCR duplicates: if multiple read pairs have identical external coordinates, only retain the pair with highest mapping quality. In the paired-end mode, this command ONLY works with FR orientation and requires ISIZE is correctly set. It does not work for unpaired reads
Usage: samtools rmdup [-sS] <input.srt.bam> <out.bam>
Trimmomatic
Function: Trimmomatic performs a variety of useful trimming tasks for illumina single ended data.
Usage: java -jar <path to trimmomatic jar> SE [-threads <threads>] [-phred33 | -phred64] [-trimlog <logFile>] <input> <output> <step 1> ... or java -classpath <path to trimmomatic jar> org.usadellab.trimmomatic.TrimmomaticSE [-threads <threads>] [-phred33 | -phred64] [-trimlog <logFile>] <input> <output> <step 1> ...
geneBody_coverage.py
Function: Calculate the RNA-seq reads coverage over gene body.
Usage: geneBody_coverage.py -r hg19.housekeeping.bed -i test.bam -o output
Trimmomatic
Function: Trimmomatic performs a variety of useful trimming tasks for illumina paired-end data.
Usage: java -jar <path to trimmomatic.jar> PE [-threads <threads] [-phred33 | -phred64] [-trimlog <logFile>] >] [-basein <inputBase> | <input 1> <input 2>] [-baseout <outputBase> | <unpaired output 1> <paired output 2> <unpaired output 2> <step 1> ... or java -classpath <path to trimmomatic jar> org.usadellab.trimmomatic.TrimmomaticPE [-threads <threads>] [-phred33 | -phred64] [-trimlog <logFile>] [-basein <inputBase> | <input 1> <input 2>] [-baseout <outputBase> | <paired output 1> <unpaired output 1> <paired output 2> <unpaired output 2> <step 1> ...
maq bfq2fastq
Function: Convert Maq’s BFQ format to standard FASTQ format.
Usage: maq bfq2fastq in.read.bfq out.read.fastq
maq fastq2bfq
Function: Convert reads in FASTQ format to Maq’s BFQ (binary FASTQ) format.
Usage: maq fastq2bfq [-n nreads] in.read.fastq out.read.bfq|out.prefix
geneBody_coverage.py
Function: Calculate the RNA-seq reads coverage over gene body.
Usage: geneBody_coverage.py -r hg19.housekeeping.bed -i test1.bam,test2.bam,test3.bam -o output
sickle
Function: Sickle is a tool that uses sliding windows along with quality and length thresholds to determine when quality is sufficiently low to trim the 3'-end of reads and also determines when the quality is sufficiently high enough to trim the 5'-end of reads. It will also discard reads based upon the length threshold. It takes the quality values and slides a window across them whose length is 0.1 times the length of the read. If this length is less than 1, then the window is set to be equal to the length of the read. Otherwise, the window slides along the quality values until the average quality in the window rises above the threshold, at which point the algorithm determines where within the window the rise occurs and cuts the read and quality there for the 5'-end cut. Then when the average quality in the window drops below the threshold, the algorithm determines where in the window the drop occurs and cuts both the read and quality strings there for the 3'-end cut. However, if the length of the remaining sequence is less than the minimum length threshold, then the read is discarded entirely (or replaced with an "N" record). 5'-end trimming can be disabled.
Usage: sickle pe -t [solexa|illumina|sanger] -f forward_reads.fastq -r reverse_reads.fastq -o trimmed_output_file1.fastq -p trimmed_output_file2.fastq -s trimmed_singles_file.fastq
PRINSEQ
Function: PRINSEQ is a tool that generates summary statistics of sequence and quality data and that is used to filter, reformat and trim next-generation sequence data. It is particular designed for 454/Roche data, but can also be used for other types of sequence data. PRINSEQ is available through a user-friendly web interface or as standalone version. The standalone version is primarily designed for data preprocessing and does not generate summary statistics in graphical form.
Usage: prinseq-lite.pl [-fasta|-fastq] input_reads.[fasta|fastq] -out_format [1|2|3|4|5] [options]