Bolger, A. M., Lohse, M., & Usadel, B. (2014). Trimmomatic: A flexible trimmer for Illumina Sequence Data. Bioinformatics, btu170.
starting on version 0.40 we also offer a github page (as well as older versions)
Version 0.39: binary, source and manual
Version 0.36: binary and source
With most new data sets you can use gentle quality trimming and adapter clipping.
You often don't need leading and traling clipping. Also in general setting keepBothReads to True can be useful when working with paired end data, you will keep even redunfant information but this likely makes your pipelines more manageable. Note the additional :2 in front of True (for keepBothReads) this is the minimum adapter length in palindrome mode, you can even set this to 1. (Default is a very conservative 8)
If you have questions please don't hesitate to contact us, this is not necessarily one size fits all. (e.g. RNAseq expression analysis vs DNA assembly).
java -jar trimmomatic-0.39.jar PE input_forward.fq.gz input_reverse.fq.gz output_forward_paired.fq.gz output_forward_unpaired.fq.gz output_reverse_paired.fq.gz output_reverse_unpaired.fq.gz ILLUMINACLIP:TruSeq3-PE.fa:2:30:10:2:True LEADING:3 TRAILING:3 MINLEN:36
for reference only (less sensitive for adapters)
java -jar trimmomatic-0.35.jar PE -phred33 input_forward.fq.gz input_reverse.fq.gz output_forward_paired.fq.gz output_forward_unpaired.fq.gz output_reverse_paired.fq.gz output_reverse_unpaired.fq.gz ILLUMINACLIP:TruSeq3-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36
This will perform the following:
java -jar trimmomatic-0.35.jar SE -phred33 input.fq.gz output.fq.gz ILLUMINACLIP:TruSeq3-SE:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36
This will perform the same steps, using the single-ended adapter file
Trimmomatic performs a variety of useful trimming tasks for illumina paired-end and single ended data.The selection of trimming steps and their associated parameters are supplied on the command line.
The current trimming steps are:
It works with FASTQ (using phred + 33 or phred + 64 quality scores, depending on the Illumina pipeline used), either uncompressed or gzipp'ed FASTQ. Use of gzip format is determined based on the .gz extension.
For single-ended data, one input and one output file are specified, plus the processing steps. For paired-end data, two input files are specified, and 4 output files, 2 for the 'paired' output where both reads survived the processing, and 2 for corresponding 'unpaired' output where a read survived, but the partner read did not.
Since version 0.27, trimmomatic can be executed using -jar. The 'old' method, using the explicit class, continues to work.
java -jar <path to trimmomatic.jar> PE [-threads <threads] [-phred33 | -phred64] [-trimlog <logFile>] <input 1> <input 2> <paired output 1> <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>] <input 1> <input 2> <paired output 1> <unpaired output 1> <paired output 2> <unpaired output 2> <step 1> ...
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> ...
If no quality score is specified, phred-64 is the default. This will be changed to an 'autodetected' quality score in a future version.
Specifying a trimlog file creates a log of all read trimmings, indicating the following details:
Multiple steps can be specified as required, by using additional arguments at the end.
Most steps take one or more settings, delimited by ':' (a colon)
Step options:
Trimming occurs in the order which the steps are specified on the command line. It is recommended in most cases that adapter clipping, if required, is done as early as possible.
Illumina adapter and other technical sequences are copyrighted by Illumina,but we have been granted permission to distribute them with Trimmomatic. Suggested adapter sequences are provided for TruSeq2 (as used in GAII machines) and TruSeq3 (as used by HiSeq and MiSeq machines), for both single-end and paired-end mode. These sequences have not been extensively tested, and depending on specific issues which may occur in library preparation, other sequences may work better for a given dataset.
To make a custom version of fasta, you must first understand how it will be used. Trimmomatic uses two strategies for adapter trimming: Palindrome and Simple
With 'simple' trimming, each adapter sequence is tested against the reads, and if a sufficiently accurate match is detected, the read is clipped appropriately.
'Palindrome' trimming is specifically designed for the case of 'reading through' a short fragment into the adapter sequence on the other end. In this approach, the appropriate adapter sequences are 'in silico ligated' onto the start of the reads, and the combined adapter+read sequences, forward and reverse are aligned. If they align in a manner which indicates 'read-through', the forward read is clipped and the reverse read dropped (since it contains no new data).
Naming of the sequences indicates how they should be used. For 'Palindrome' clipping, the sequence names should both start with 'Prefix', and end in '/1' for the forward adapter and '/2' for the reverse adapter. All other sequences are checked using 'simple' mode. Sequences with names ending in '/1' or '/2' will be checked only against the forward or reverse read. Sequences not ending in '/1' or '/2' will be checked against both the forward and reverse read. If you want to check for the reverse-complement of a specific sequence, you need to specifically include the reverse-complemented form of the sequence as well, with another name.
The thresholds used are a simplified log-likelihood approach. Each matching base adds just over 0.6, while each mismatch reduces the alignment score by Q/10. Therefore, a perfect match of a 12 base sequence will score just over 7, while 25 bases are needed to score 15. As such we recommend values between 7 - 15 for this parameter. For palindromic matches, a longer alignment is possible - therefore this threshold can be higher, in the range of 30. The 'seed mismatch' parameter is used to make alignments more efficient, specifying the maximum base mismatch count in the 'seed' (16 bases). Typical values here are 1 or 2.