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Utitilies for constructing and manipulating models for non-local structural dependencies in genomic sequences
Readme
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:
COVID-19 | INFLUENZA |
---|---|
Compute a structure-aware evolution-adaptive notion of distance between genomes, which is demonstrably more biologically relevant compared to the standard edit distance.
Draw samples in-silico that have a high probability of being biologically correct. For example, given a database of Influenza sequences, we can generate a new genomic sequence that has a high probability of being a valid influenza sequence.
To install with pip:
pip install quasinet
To fix error with Mac or Windows:
from quasinet.osfix import osfix
# for windows
osfix('win')
# for max x86_64 (macbook pro)
osfix('macx86')
# mac arm (macbook air)
osfix('macarm')
NOTE: If trying to reproduce the paper below, please use pip install quasinet==0.0.58
from quasinet import qnet
# initialize qnet
myqnet = qnet.Qnet()
# train the qnet
myqnet.fit(X)
# compute qdistance
qdist = qnet.qdistance(seq1, seq2, myqnet, myqnet)
Examples are located here.
For more documentation, see here.
For reference, please check out our paper:
You can reach the ZED lab at: zed.uchicago.edu
FAQs
Utitilies for constructing and manipulating models for non-local structural dependencies in genomic sequences
We found that quasinet demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 3 open source maintainers collaborating on the project.
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