Next generation sequencing (NGS) data is notably huge in file size. Dealing with NGS data is not only time consuming but also puts constraints on hard disk space. This is especially true if analysis parameters need to be optimized. The Subsample FASTQ function is a very useful tool to get a subset of the raw data upon which optimization can be performed. The optimized parameters can then be saved and applied to the whole dataset

Subsample FASTQ is only available for unaligned reads of FASTQ format. To trigger this function, select the Unaligned Reads data node and select Subsample FASTQ from the Pre-alignment tools section on the menu. Then specify how many reads you want to keep for every nth reads. For example: if the user specifies to "Keep one read for every 10 reads" (Figure 1), this means that for every 10 reads, the program will keep only 1 read. This is equivalent to keeping 10% of the data. 

Figure 1. Subsample FASTQ page. This option shows getting a subset of raw data by keeping one read for every 10 reads.

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