quasinet 0.0.33

Utitilies for constructing and manipulating models for non-local structural dependencies in genomic sequences

Author:

ZeD@UChicago <zed.uchicago.edu>

Description:

Infer Non-local Structural Dependencies In Genomic Sequences. Genomic sequences are esentially compressed encodings of phenotypic information. This package provides a novel set of tools to extract long-range structural dependencies in genotypic data that define the phenotypic outcomes. The key capabilities implemented here are as follows: 1. computing the q-net given a databse of nucleic acid sequences, which is a family of conditional inference trees capturing the predictability of each nucleotide position given the rest of the genome. 2. Computing a structure-aware evolution-adaptive notion of distance between genomes, which demonstrably is much more biologically relevant compared to the standard edit distance 3. Ability to draw samples in-silico, that have a high probability of being biologically correct. For example, given a database of HIV sequences, we can generate a new genomic sequence, which has a high probability of being a valid encoding of a HIV virion. The constructed q-net for long term non-progressor clinical phenotype in HIV-1 infection is shown below.