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We found that the sequencing data quality that was acquired by 'image-flags' was consistently poorer than bareback-processed data, as analysed by either per-base or per-sequence Phred quality scores (Fig. S1).
Sequencing data quality control was performed prior to data analysis.
Sequencing data quality was assessed using FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/).ac.uk/projects/fastqc/
An interesting finding from this study is that sequencing data and genotyping chip consistency might not represent the whole picture of sequencing data quality, as we previously thought.
Owing to the proprietary data formats, all the sequencing data quality control, alignment, and variant calling were performed by CG as part of their sequencing service, using their version 2.0 pipeline [ 16].
While we have not noticed any obvious decrease in the sequencing data quality when SYBR Green is included in the PCR step, one alternative to avoid this would be to amplify half the adapter-ligated DNA using real-time PCR to determine cycle number, and repeat the reaction without SYBR Green using the remaining sample.
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Phred [39]was used to assess sequence data quality and ClustalW [40] was used to align multiple sequences and identify polymorphisms.
Next, we investigated whether the amount of starting material affected sequence data quality.
RNA sequence data quality was checked using FastQC and was cleaned using TRIMMOMATIC v0.27 [ 25].
Sequence data quality has also been improved with the use of multiple search engines for database searching.
Most importantly for forensics, haplogroup assignment has proven to be an important tool for sequence data quality control [8].
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