By comparing and contrasting data generated with three low-input RNA sequencing methods, a California team has characterized the technical variations introduced at increasingly lower RNA levels, while considering ways to mitigate that variation in the future.

"My goal in this comparison was two-fold," Shankar Subramaniam, a bioinformatics, systems biology, and bioengineering researcher at the University of California, San Diego, told In Sequence.

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