It is well established that extreme base composition is associated with bias in multiple technologies [3,4,6,13,14,19-22,27]. In this work, we define specific base composition categories that are associated with bias, which we refer to as 'motifs'. Motif bias statistics can be measured accurately with much less data than per-base statistics (see below). They are also valuable because they can suggest underlying causes of bias that can then be investigated in laboratory experiments and can be used to track performance of attempted process improvements.
