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Three general clusters were generated based on informative SNPs that grouped by SGA levels for most of the accessions.
In brief, fragmented cDNA was fixed to a flow cell, and clusters were generated using a Paired-End Cluster Generation Kit v4 (Illumina).
Clusters were generated using Illumina's Single Read Cluster Generation Kit v4 (GD-103-4001) or Paired End Cluster Generation Kit v4 (PE-203-4001), respectively.
Clusters were generated separately using three different mechanisms, namely, (1) the hidden factor data generation approach, (2) 1-dependent approach, and (3) 2-dependent approach.
Clusters were generated using OCG13 and default options.
Five clusters were generated from albumins, six from globulins and four from prolamins patterns.
While it is true that clusters were generated through an automated process, the clustering objective was underpinned by a rigorous, medicinal chemistry based structural rule set.
A total of 40 clusters were generated, 23 of which have more than three members.
The clusters were generated by UPGMA (average score clustering) and similarity measures assessed using Euclidean distance.
Schematic representations of the clusters were generated using custom software with the pre-calculated information above.
Using MultiExperiment Viewer [52] eight hard clusters were generated using seven cycles with a maximum diversity of 0.8.
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