Abstract: Techniques for automated determination or correction of count bias are based on nucleic acid base content on a finer grained scale than a bin of interest in a target sequence. The techniques include obtaining a target sequence with bins where relative abundances indicate a condition and raw counts Hj of reads, from a subject, which start at each locus j. A partition indicates a fine-grained window at a position relative to a current locus and multiple strata indicating different base contents. Each locus is attributed to one stratum k(j). An expected count of each stratum, E(k), is determined based on Hj for j belonging to the stratum and a number of loci in the target belonging to the stratum. A copy number of a bin is based on a sum of E(k(j)) in the bin. Output data indicates condition of the subject based at least partly on the copy number.

Abstract: Techniques for construction of internal controls for improved accuracy and sensitivity of DNA testing include obtaining first data and determining weights over real numbers for a normalization function in less than a day. The first data indicates a measured amount of reference sequences for nucleic acids from training samples. The reference sequences include a target, for which an abundance is indicative of a condition of interest, and covariates not correlated with the condition of interest. The normalization function involves a sum of abundances of the covariates, as internal controls, each multiplied by a corresponding one of the weights. The weights are determined based on minimizing variance of a Taylor expansion of a ratio of a measured amount of the target divided by a value of the normalization function evaluated with measured amounts of the covariates over a portion of the first data in which the condition is absent.