Yohei Rosen | Searcharxiv

arXiv2023

Statdepth: a package for analysis of functional and pointcloud data using statistical depth

Laboratory scientists are well equipped with statistical tools for univariate data, yet many phenomena of scientific interest are time-variant or otherwise multidimensional. Functional data analysis is one way of approaching such data: by representing these more complex data as single data points in a mathematical space of functions. The mathematical concept of functional depth provides a notion of centrality which allows for descriptive statistics and some comparative statistics on these data. Here, we present statdepth, a Python package for functional depth-based analyses which naturally extends familiar single-data-point L-statistics and related methods to time-variant data trajectories or multidimensional data.

stat.CO↗

arXiv2015

Canonical, Stable, General Mapping using Context Schemes

Motivation: Sequence mapping is the cornerstone of modern genomics. However, most existing sequence mapping algorithms are insufficiently general. Results: We introduce context schemes: a method that allows the unambiguous recognition of a reference base in a query sequence by testing the query for substrings from an algorithmically defined set. Context schemes only map when there is a unique best mapping, and define this criterion uniformly for all reference bases. Mappings under context schemes can also be made stable, so that extension of the query string (e.g. by increasing read length) will not alter the mapping of previously mapped positions. Context schemes are general in several senses. They natively support the detection of arbitrary complex, novel rearrangements relative to the reference. They can scale over orders of magnitude in query sequence length. Finally, they are trivially extensible to more complex reference structures, such as graphs, that incorporate additional variation. We demonstrate empirically the existence of high performance context schemes, and present efficient context scheme mapping algorithms. Availability and Implementation: The software test framework created for this work is available from https://registry.hub.docker.com/u/adamnovak/sequence-graphs/. Contact: benedict@soe.ucsc.edu Supplementary Information: Six supplementary figures and one supplementary section are available with the online version of this article.

q-bio.GN↗