ngs library prep automation: the throughput at which ngs automation pays, what it fixes, and the tracking that has to survive every plate transfer

Judging the case

1. Throughput is the threshold. Below a steady flow of plates, a good technician is faster, cheaper and more adaptable than a platform that needs setup and maintenance for each run. Above it, automation wins on consistency as much as on hands-on time. Measure your actual sustained throughput rather than your peak.
2. Consistency is the real gain. Automated preparation reduces variation between samples and between operators, which shows up as more even coverage and fewer failed libraries. For anything quantitative or for long studies, this is worth more than the time saved.
3. Index assignment must be traceable. Every sample gets an index, and a mis-assigned index produces data attributed to the wrong sample, which is worse than a failed run because nothing looks wrong. The plate map, the index set and the system of record must be linked without anybody typing anything.
4. Kit and deck compatibility. Automated protocols are validated by kit suppliers for particular platforms, and running an unvalidated combination means you validate it. Confirm which kits have supported scripts on the platform you are considering, and whether the whole protocol fits on the deck.
5. Quantification and normalisation steps. Library quantification and pooling to equal molarity are the steps that decide whether samples are evenly represented. Ask whether the platform performs them, since a workflow automated up to that point and manual afterwards keeps the bottleneck it set out to remove.

Contamination and index hopping

Automation concentrates amplified material on one deck, and cross-contamination between wells or from previous runs produces low-level signals that are easy to misread. Filtered tips, deliberate plate layouts with no-template controls, and a cleaning regime are part of the method.

Unique dual indexes address index hopping and misassignment far better than single indexes, and on an automated high-throughput workflow they are worth the additional cost.

What to test during evaluation

Run your own kit, on your own sample types, on a full plate, and compare library yield, size distribution and coverage evenness against your manual process. A vendor demonstration with their kit on their samples proves the robot moves liquid.

Include a deliberately difficult sample type. Automation handles the easy cases first and the difficult ones are where you will discover whether it suits your laboratory.

Common questions

At what throughput does library prep automation pay?

Above a sustained flow of plates rather than an occasional peak. Below that, a good technician is faster, cheaper and more adaptable than a platform needing setup and maintenance per run.

What is the main benefit?

Consistency between samples and operators, which shows as more even coverage and fewer failed libraries. For quantitative work and long studies that is worth more than the hands-on time saved.

How do I avoid index misassignment?

Link the plate map, the index set and the system of record without manual transcription, and use unique dual indexes. A mis-assigned index produces data attributed to the wrong sample with nothing looking wrong.

What should I test in an evaluation?

Your own kit on your own samples over a full plate, including a difficult sample type, compared against your manual process on library yield, size distribution and coverage evenness.

Browse by service class

• Compare Gene synthesis on advertised prices