Edit me

Step 1.2: Quality trimming

Once the adapters have been trimmed, it is useful to inspect the quality of reads in bulk, and try to trim low quality nucleotides 1. Also, frequently the quality tends to drop off toward one end of the read. FASTQC 2 and PrinSeq 3 will show that very nicely . These read ends with low average quality can then be trimmed, if desired, using Trimmomatic 4, FASTX-Toolkit fastq_quality_filter, PrinSeq, or SolexaQA 5.

Bibliography

  1. Del Fabbro, C., Scalabrin, S., Morgante, M. & Giorgi, F. M. An extensive evaluation of read trimming effects on Illumina NGS data analysis. PLoS ONE 8, e85024 (2013). 

  2. Babraham Bioinformatics - FastQC A Quality Control tool for High Throughput Sequence Data. at http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ 

  3. Schmieder, R. & Edwards, R. Quality control and preprocessing of metagenomic datasets. Bioinformatics 27, 863–864 (2011). 

  4. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014). 

  5. Cox, M. P., Peterson, D. A. & Biggs, P. J. SolexaQA: At-a-glance quality assessment of Illumina second-generation sequencing data. BMC Bioinformatics 11, 485 (2010).