Multiple indexes per sample how to trim with Trimmomatic?!

[Tsequencing]

Hi all,

I received my HiSeq Illumina RNAseq data and want to run trimmomatic to remove bad quality reads and trim adapters. I have used trimmomatic before but I am currently in doubt if I create the adapter file in a correct way, can someone please correct me if I'm wrong?

Sequencing happened on Illumina HiSeq4000 using NEBnext kit for the library construction.

From the sequencing facility I have received the adapter and index sequences (e.g for my first sample):

Adapter:

5' Adapter: 5'-AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCT-3'

3' Adapter(lowercase 6bp bases is Index) 5'-GATCGGAAGAGCACACGTCTGAACTCCAGTCACatcacgATCTCGTATGCCGTCTTCTGCTTG-3

index:
CTGGCATA;CGGCTATG

- I do not understand why I receive two indexes for a single sample? A single sample, needs only one adapter with one specific index? Correct?

- Trimmomatic needs an adapter file and I will create as follows (with all adapters and indeces in a single file):

>Prefix_AdapterPE1/1
AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCT
>Prefix_AdapterPE1/2
GATCGGAAGAGCACACGTCTGAACTCCAGTCACctggcataATCTCGTATGCCGTCTTCTGCTTG

With the index in capitals also, but just to show that I will manually add the index sequence. I will do this for all received index sequences, added to a single adapter file and will finally run Trimmomatic.

Any comments are welcome!

[ashishbansal]

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:

ILLUMINACLIP: Cut adapter and other illumina-specific sequences from the read.
SLIDINGWINDOW: Perform a sliding window trimming, cutting once the average quality within the window falls below a threshold.
LEADING: Cut bases off the start of a read, if below a threshold quality
TRAILING: Cut bases off the end of a read, if below a threshold quality
CROP: Cut the read to a specified length
HEADCROP: Cut the specified number of bases from the start of the read
MINLEN: Drop the read if it is below a specified length
TOPHRED33: Convert quality scores to Phred-33
TOPHRED64: Convert quality scores to Phred-64
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.