In typical large-scale studies of 5,000 samples, Stanford researchers estimated it would take RNA-Seq 10 times longer to analyze one percent of the number of genes processed by the new array and 20 times longer to analyze one-half percent of exons. Moreover, to achieve the same level of reproducibility as the new array, RNA-Seq would require 150 million mappable reads for genes and 200 million for exons (3711).(1) Based on this level of power and performance, the researchers concluded the Human Transcriptome Array is more reproducible, faster, and cost-effective than RNA-Seq for detecting and characterizing low-level expression changes of clinically relevant transcripts.
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