Methods for flow space quality score prediction by neural networks

A system for estimating quality values of nucleotide base calls, comprising:

• a machine-readable memory;
• and
• a processor configured to execute machine-readable instructions, which, when executed by the processor, cause the system to perform a method, comprising:
• receiving, at the processor, flow space signal measurements from a reaction confinement region, the flow space signal measurements generated in response to a nucleotide flow to the reaction confinement region in an array of reaction confinement regions;
• generating a base call and a plurality of flow predictor features corresponding to the nucleotide flow based on the flow space signal measurements, wherein the plurality of flow predictor features include feature vectors generated per flow;
• applying an artificial neural network to the plurality of flow predictor features to generate a flow space probability of error;
• and
• determining a base quality value based on the flow space probability of error.

A non-transitory machine-readable storage medium comprising instructions which, when executed by a processor, cause the processor to perform a method for estimating quality values of nucleotide base calls, comprising:

• receiving, at the processor, flow space signal measurements from a reaction confinement region, the flow space signal measurements generated in response to a nucleotide flow to the reaction confinement region in an array of reaction confinement regions;
• generating a base call and a plurality of flow predictor features corresponding to the nucleotide flow based on the flow space signal measurements, wherein the plurality of flow predictor features include feature vectors generated per flow;
• applying an artificial neural network to the plurality of flow predictor features to generate a flow space probability of error;
• and
• determining a base quality value based on the flow space probability of error.