SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data.

Eric M DavisYu SunYanling LiuPandurang KolekarYing ShaoKarol SzlachtaHeather L MulderDongren RenStephen V RiceZhaoming WangJoy NakitandweAlexander M GoutBridget ShanerSalina HallLeslie L RobisonStanley PoundsJeffery M KlcoJohn EastonXiaotu Ma

Published in: Genome biology (2021)

Our study reveals novel insights into the nature of DNA sequencing errors incurred on DNA sequencers. Our method can be used to assess, calibrate, and monitor sequencer accuracy, and to computationally suppress sequencer errors in existing datasets.

Keyphrases

circulating tumor
patient safety
adverse drug
cell free
single molecule
electronic health record
circulating tumor cells
single cell
rna seq
big data
emergency department
machine learning
quality improvement
artificial intelligence