The present disclosure provides methods and systems for detecting
colorectal cancer by
nucleic acid methylation analysis. In particular, the present disclosure provides methods and systems for screening or detecting
colorectal cancer or subsequent colorectal
disease progression, which can be applied to
cell-free nucleic acids, such as
cell-
free DNA. The method may
train a
machine learning model using detection of
methylation signals within a single sequencing read in an identified genomic region as an input feature and generate a classifier suitable for layering a
population of individuals. The method may include extracting
DNA from a
cell-free sample obtained from a subject, transforming the
DNA for
methylation sequencing, generating a sequencing read, and detecting a colonic proliferative cell disorder related
signal in sequencing information, and training a
machine learning model to provide a
discriminator, the
discriminator is capable of differentiating groups, such as health,
cancer, or differentiating
disease subtypes or stages, in a
population of subjects. The methods are useful, for example, in predicting, prognosing, and / or monitoring
response to treatment,
tumor load, recurrence, or progression of
colorectal cancer.