Abstract: Provided herein are methods and kits for measuring fragment size distribution of DNA fragments from a sample of a subject, for the purposes of cancer or tumor detection, characterization, and/or management.

Abstract: Provided is a computer-implemented method, including inputting to a trained machine learning classifier genomic information of a non-training subject that includes features from a tumor sample, wherein the trained machine learning classifier trained on features of tumor samples obtained from training subjects and their a responsiveness to checkpoint inhibition treatment and the machine-learning classifier is trained to predict responsiveness to the treatment, and generating a checkpoint inhibition responsiveness classification predictive of the subject's responding to the checkpoint inhibition with the trained machine-learning classifier, and reporting the checkpoint inhibition responsiveness classification using a graphical user interface. Also provided are a computer system for performing the method and a machine learning classifier trained by the method.

Abstract: Provided is a computer-implemented method, including inputting to a trained machine learning classifier genomic information of a non-training subject that includes features from a tumor sample, wherein the trained machine learning classifier trained on features of tumor samples obtained from training subjects and their a responsiveness to checkpoint inhibition treatment and the machine-learning classifier is trained to predict responsiveness to the treatment, and generating a checkpoint inhibition responsiveness classification predictive of the subject's responding to the checkpoint inhibition with the trained machine-learning classifier, and reporting the checkpoint inhibition responsiveness classification using a graphical user interface. Also provided are a computer system for performing the method and a machine learning classifier trained by the method.