Selecting a node with unaligned reads (either Unaligned reads or Trimmed reads) shows the QA/QC section in the toolbox, with two options (Figure 1). To assess the quality of your raw reads, use Pre-alignment QA/QC.
If selected, K-mer length creates a per-sample report with the position of the most frequent k-mers (i.e. sequences of k nucleotides) of the length specified in the dialog. The range of input values is from one to 10.
The last control refers to .fastq files. Partek Flow can automatically detect the quality encoding scheme (Auto detect) or you can use one of the options available in the drop-down list. However, the auto-detection is only applicable for Phred+33 and Phred+64 type of quality encoding score. For early version of Solexa quality encoding score, select Solexa+64 from the Quality encoding drop down list. For a paired-end data, the pre-alignment QA/QC will be done on each read in pair separately and the results will be shown separately as well.
The task report is organised in two tiers. The initial view shows project-level report with all the samples. An overview table is at the top, while matching plots are below.
The Pre-alignment QA/QC output table contains one input file per row, with typical metrics on columns (%GC: fraction of GC content; %N: fraction of no-calls) (Figure 3). The file names are hyperlinks, leading to the sample-level reports. To save the table as a txt file to a local computer, push the Download link. Table columns can be sorted using double arrows icon ().
Two project-level plots are Average base quality per position and Average base quality score per read (Figure 4). The latter plot presents the proportion of reads (y-axis) with certain average quality score (meaning all the base qualities within a read are averaged; x-axis). Mouse over a data point to get the matching readouts. The Save icon saves the plot in a .svg format to the local machine. Each line on the plot represents a data file and you can select the sample names from the legend to hide/un-hide individual lines.
Base composition plot specifies relative abundance of each base per position (Figure 6), with N standing for no-calls. By selecting individual bases on the legend, you can remove them from the plot / bring them back on. To zoom in, left-click & drag over a region of interest. To zoom out, use the Reset button () to recreate the original view, or the magnifier glass () to zoom out one level.
Additional Assistance
If you need additional assistance, please visit our support page to submit a help ticket or find phone numbers for regional support.
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