Machine learning techniques to determine base methylations

A method for detecting a methylation of a nucleotide in a nucleic acid molecule, the method comprising:

• receiving a first plurality of first data structures, each first data structure of the first plurality of first data structures corresponding to a respective window of positions around a respective target position of nucleotides sequenced in a respective nucleic acid molecule of a plurality of first nucleic acid molecules, wherein each of the first nucleic acid molecules is sequenced by measuring pulses in a signal corresponding to the nucleotides, wherein the methylation has a known first state in a nucleotide at the respective target position in each window of each first nucleic acid molecule, each first data structure comprising values for one or more signal properties at positions within the respective window;
• storing a plurality of first training samples, each first training sample including one of the first plurality of first data structures and a first label indicating the first state of the nucleotide at the respective target position;
• and
• training a model by:
• filtering the first plurality of first data structures through one or more convolutional layers to obtain a plurality of convolutional matrices,
• applying a transformer layer to the plurality of convolutional matrices to obtain transformer matrices, wherein applying the transformer layer to a convolutional matrix includes generating a plurality of attention scores that quantify a relevance among positions of the convolutional matrices,
• generating methylation probabilities at respective target positions of the first plurality of first data structures using the transformer matrices,
• determining outputs using the methylation probabilities, and
• optimizing, using the plurality of first training samples, parameters of the model based on the outputs of the model matching or not matching corresponding labels of the first labels when the first plurality of first data structures is input to the model, wherein an output of the model specifies whether the nucleotide at the respective target position in the respective window has the methylation, wherein the parameters of the model include the plurality of attention scores.

A method for detecting a methylation of a nucleotide in a nucleic acid molecule, the method comprising:

• receiving a first plurality of first data structures, each first data structure of the first plurality of first data structures corresponding to a respective window around a respective target position of nucleotides sequenced in a respective nucleic acid molecule of a plurality of first nucleic acid molecules, wherein each of the first nucleic acid molecules is sequenced by measuring pulses in a signal corresponding to the nucleotides, wherein each first nucleic acid molecule comprises a training sample nucleic acid molecule and a first adaptor having a known sequence, wherein the methylation has a known first state in a nucleotide at the respective target position in a portion of each window of each first nucleic acid molecule corresponding to the training sample nucleic acid molecule, each first data structure comprising values for one or more signal properties;
• storing a plurality of first training samples, each including one of the first plurality of first data structures and a first label indicating the first state of the nucleotide at the respective target position, and
• training a model by optimizing, using the plurality of first training samples, parameters of the model based on outputs of the model matching or not matching corresponding labels of the first labels when the first plurality of first data structures is input to the model, wherein an output of the model specifies whether the nucleotide at the respective target position in the respective window has the methylation.