Information theory improves genetic analysis of complex traits
Claim that applying information theoretic frameworks can better capture complex genetic phenomena such as dominance and gene interactions, compared to standard additive/independence models.
Evidence Quote
“An information theoretic framework for analyzing trait variation can better capture phenomena like allelic dominance and gene-gene interaction.”
Relationship
Connections (6)
Evidence
“Reference to a method for modeling microbial abundances using beta-binomial regression.”
“Citation for the phyloseq R package for microbiome data analysis.”
“Citation for the Metacoder R package for community taxonomic diversity analysis.”
“Citation for the sourmash library used for MinHash sketching of DNA.”
“Reference for LINflow computational pipeline for prokaryotic genome similarity matrices.”
“Reference to Steinegger and Söding 2018 about linear-time clustering of protein sequence sets”
“Reference to Buchfink, Reuter, Drost 2021 on DIAMOND for protein alignment”
“Reference to Boratyn et al. 2013 describing improvements to BLAST”
“Reference to Köster and Rahmann 2012 describing the Snakemake workflow engine”
“Reference to csvtk toolkit by Shen W”
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“Review on selection decisions and breeding program futures”