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sickle - A windowed adaptive trimming tool for FASTQ files using quality

About

Most modern sequencing technologies produce reads that have deteriorating quality towards the 3'-end and some towards the 5'-end as well. Incorrectly called bases in both regions negatively impact assembles, mapping, and downstream bioinformatics analyses.

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. 5'-end trimming can be disabled.

Sickle also has an option to discard reads with any Ns in them.

Sickle supports three types of quality values: Illumina, Solexa, and Sanger. Note that the Solexa quality setting is an approximation (the actual conversion is a non-linear transformation). The end approximation is close. Illumina quality refers to qualities encoded with the CASAVA pipeline between versions 1.3 and 1.7. Illumina quality using CASAVA >= 1.8 is Sanger encoded.

Note that Sickle will remove the 2nd fastq record header (on the "+" line) and replace it with simply a "+". This is the default format for CASAVA >= 1.8.

Sickle also supports gzipped file inputs. There is also a sickle.xml file included in the package that can be used to add sickle to your local Galaxy server.

Requirements

Sickle requires a C compiler; GCC or clang are recommended. Sickle relies on Heng Li's kseq.h, which is bundled with the source.

Sickle also requires Zlib, which can be obtained at http://www.zlib.net/.

Building and Installing Sickle

To build Sickle, enter:

make

Then, copy or move "sickle" to a directory in your $PATH.

Usage

Sickle has two modes to work with both paired-end and single-end reads: sickle se and sickle pe.

Running sickle by itself will print the help:

sickle

Running sickle with either the "se" or "pe" commands will give help specific to those commands:

sickle se
sickle pe

Sickle Single End (sickle se)

sickle se takes an input fastq file and outputs a trimmed version of that file. It also has options to change the length and quality thresholds for trimming, as well as disabling 5'-trimming and enabling removal of sequences with Ns.

Examples

sickle se -f input_file.fastq -t illumina -o trimmed_output_file.fastq
sickle se -f input_file.fastq -t illumina -o trimmed_output_file.fastq -q 33 -l 40
sickle se -f input_file.fastq -t illumina -o trimmed_output_file.fastq -x -n

Sickle Paired End (sickle pe)

sickle pe can operate with two types of input. First, it can take two paired-end files as input and outputs two trimmed paired-end files as well as a "singles" file. The second form starts with a single combined input file of reads where you have already interleaved the reads from the sequencer. In this form, you also supply a single output file name as well as a "singles" file. The "singles" file contains reads that passed filter in either the forward or reverse direction, but not the other. You can also change the length and quality thresholds for trimming, as well as disable 5'-trimming and enable removal of sequences with Ns.

Examples

sickle pe -f input_file1.fastq -r input_file2.fastq -t sanger \
-o trimmed_output_file1.fastq -p trimmed_output_file2.fastq \
-s trimmed_singles_file.fastq

sickle pe -f input_file1.fastq -r input_file2.fastq -t sanger \
-o trimmed_output_file1.fastq -p trimmed_output_file2.fastq \
-s trimmed_singles_file.fastq -q 12 -l 15

sickle pe -f input_file1.fastq -r input_file2.fastq -t sanger \
-o trimmed_output_file1.fastq -p trimmed_output_file2.fastq \
-s trimmed_singles_file.fastq -n

sickle pe -c combo.fastq -t sanger -m combo_trimmed.fastq \
-s trimmed_singles_file.fastq -n