Abstract: This disclosure describes methods, non-transitory computer readable media, and systems that can train a genome-location-classification model to classify or score genomic coordinates or regions by the degree to which nucleobases can be accurately identified at such genomic coordinates or regions. For instance, the disclosed systems can determine sequencing metrics for sample nucleic-acid sequences or contextual nucleic-acid subsequences surrounding particular nucleobase calls. By leveraging ground-truth classifications for genomic coordinates, the disclosed systems can train a genome-location-classification model to relate data from one or both of the sequencing metrics and contextual nucleic-acid subsequences to confidence classifications for such genomic coordinates or regions.

Abstract: A method for the label-free sizing of small, nanometer-sized objects such as particles includes a hand-held, portable holographic microscope that incorporates vapor condensation of nanolenses and time-resolved lens-free imaging. The portable device is used to generate reconstructed, time-resolved, and automatically-focused phase images of the sample field-of-view. The peak phase value for each object a function of working distance (z2) and condensation time (t) is used to measure object size. The sizing accuracy has been quantified in both monodisperse and heterogeneous particle solutions, achieving an accuracy of +/?11 nm for particles that range from 40 nm up to 500 nm. For larger particles, the technique still works while the accuracy roughly scales with particle size.