FastQC

Per sequence quality scores

Figure 1 : graph representing the quality score by the number of reads for each sample.

source : Babraham Training Courses

This graph allows you to evaluate the average quality of your sequences. If the average quality of the run impacts a small percentage of sequences, the distribution will be correct (acceptable error rate). If not, it means that there is a specific problem that you will need to determine.

Warning

A warning is issued if the average most frequently observed quality is less than 27 - equivalent to an error rate greater than 0.2%.

Failure

An error is triggered if the average most frequently observed quality is less than 20 - equivalent to an error rate greater than 1%.

Common reasons for warnings

Figure 2 : Diagram of the expected results