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Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.

The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
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Using automation to prepare sequencing libraries isn’t a new concept, and most researchers are aware that there are numerous benefits to automating this process. However, many labs are still hesitant to switch to automation and often believe that it’s not suitable for their lab. To combat these concerns, we’ll cover some of the key advantages, review the most important considerations, and get real-world advice from automation experts to remove any lingering anxieties....