Predicting quality of sequencing results using deep neural networks
US11288576B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 5, 2018 |
| Grant date | Mar 29, 2022 |
| Priority date | — |
| Expiry date | Sep 6, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16B40/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The technology disclosed predicts quality of base calling during an extended optical base calling process. The base calling process includes pre-prediction base calling process cycles and at least two times as many post-prediction base calling process cycles as pre-prediction cycles. A plurality of time series from the pre-prediction base calling process cycles is given as input to a trained convolutional neural network. The convolutional neural network determines from the pre-prediction base calling process cycles, a likely overall base calling quality expected after post-prediction base calling process cycles. When the base calling process includes a sequence of paired reads, the overall base calling quality time series of the first read is also given as an additional input to the convolutional neural network to determine the likely overall base calling quality after post-prediction cycles of the second read.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.