Illumina sequencing offers incredible capacity. Often, biologists wish to split this capacity among many samples run in multiplex. When you do this, and you demultiplex the samples that you run together, you generally get files output from Casava that look something like:




These names correspond to a general file structure for each sample that looks like:


where the <name> is equivalent to the species binomial name used above, the string of letters is equivalent to <sequence-tag>, the <lane> the samples were run in was Lane 5 (L005), each sample has a <read> Read1 (R1) and Read2 (R2) file because this was paired-end (PE) sequencing, and each file has only a single <read-file> (001).

When you multiplex many samples into the same lane, you can end up with many many output files (e.g. 100). But, we still need to trim adapter contamination and low quality bases from these files. Adapter contamination occurs when the insert DNA sequence is shorter than the read length, and we sequence part of the adapter during the sequencing process. Low quality bases occur as a function of read length, chemistry, the sequencing platform, etc. Removal of adapter contamination and low quality bases is essential to proper downstream analysis and processing.

The problem is that with so many files, removing adapter contamination and low quality bases is problematic across all of the files. Doing so may require tedious processing by hand (which is bad) or shell scripting, which many people are not comfortable with. When we trim adapters and remove contamination, we may also want to do things such as bulk-renaming of the sequence files and placing the resulting trimmed data in a static directory structure for downstream processing (like phyluce).

This is why I wrote illumiprocessor - it processess many input files of Illumina data, in parallel, to:

  1. rename hundreds of fastq files
  2. create a sample-specific, adapters.fasta file for adapter trimming
  3. trim adapter contamination from input fastq files
  4. trim low quality bases from input fastq files

illumiprocessor is a wrapper script around a software package written in JAVA named trimmomatic that runs trimmomatic against many Illumina fastq files in parallel.

In our hands, trimmomatic is the best adapter and quality trimmer we have used, and it is developed and maintained by Björn Usadel’s group. trimmomatic outperforms a number of other read trimmers, it is reasonably fast, and it offers a lots of nice trimming options.