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CUBScout

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Codon Usage Bias (CUB) in Julia

CUBScout helps you work with codons! Beyond counting codons and finding codon frequency, CUBScout calculates Codon Usage Bias (CUB) and related expressivity predictions. Currently, CUBScout calculates:

  • Six measures of codon usage bias:
    • B, from Karlin and Mrazek, 1996
    • ENC, from Wright 1990
    • ENC', from Novembre, 2002
    • MCB, from Urrutia and Hurst, 2001
    • MILC, from Supek and Vlahovicek, 2005
    • SCUO, from Wan et al., 2004
  • Five expressivity measures based on codon usage bias:
    • CAI, from Sharp and Li, 1987
    • E, from Karlin and Mrazek, 1996
    • FOP, from Ikemura, 1981
    • GCB, from Merkl, 2003
    • MELP, from Supek and Vlahovicek, 2005

CUBScout is based off of the fabulous coRdon package in R by Anamaria Elek, Maja Kuzman, and Kristian Vlahovicek. I am grateful for their clear code and would encourage you to cite coRdon as well when using CUBScout.

You can install CUBScout by:

using Pkg
pkg> add CUBScout

Or for the dev version:

pkg> add CUBScout#main

CUBScout is under active development, and I welcome contributions or suggestions! Additional features I'm working on/would like to incorporate:

  • Performance improvements
  • Plotting support (e.g. BPlots)
  • Additional CUB measures, including S, RCDI, CDC, RCA, RCSU, and RCBS
  • Growth predictions derived from CUB, such as those in growthpred and gRodon

cubscout.jl's People

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Thomas Poulsen avatar Hiroki Ban avatar Camilo García avatar Marco Matthies avatar John Lapeyre avatar

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jakobnissen

cubscout.jl's Issues

[RFC] Having methods for BioSequences types

Hi @gus-pendleton

This is such a nice idea to incorporate the metrics of this package! I mentioned on Slack that I'm willing to incorporate some of them in my package GeneFinder.jl in the future. Currently, GeneFinder is able to detect ORFs in a dedicated struct, and then using the BioSequences types it can get the LongSubSeq{DNAAlphabet{4}} in a vector of them, here is an example:

julia> seq = randdnaseq(10^3)

1000nt DNA Sequence:
GGGATTCACATCGTACCGCCCGGGTACCGCCGGCAACGT…TGTCAGACCCATTGAAAGGCCTATGGCATCCTGTGCAAG

Using the GeneFinder function gets() it extracts all the possible ORFs in a Vector{LongSubSeq{DNAAlphabet{4}}}:

julia> getcds(seq)

36-element Vector{LongSubSeq{DNAAlphabet{4}}}:
 ATGCCATAG
 ATGGGTCTGACACTGCAGTCACTAGTTGCTAATAACAGA…CTGTCTCATATTTCATCAGAAGTGAGACTGTGTTGTTAG
 ATGTACTCAGACGATGGTACACGCAGTCAGACACGAATAGCGGGTAATTAA
 ATGGGAATGAAGCACCAGCAGCGCCTTACAGAAGGCACC…CAAGTGTCCCGAAGCTGTCTCATATTTCATCAGAAGTGA
 ATGAAGCACCAGCAGCGCCTTACAGAAGGCACCTACCGC…CAAGTGTCCCGAAGCTGTCTCATATTTCATCAGAAGTGA
 ATGGTACACGCAGTCAGACACGAATAG
 ATGCTCATGCGACCAGTTAGACCGCAGACTCCGATAGTC…GTACAATCCCTAGTTCGGGGTTCGAGTTCTCCTAGATGA
 ATGCGACCAGTTAGACCGCAGACTCCGATAGTCCGATCG…GTACAATCCCTAGTTCGGGGTTCGAGTTCTCCTAGATGA
 ATGGGGCATTAG
 ATGGGAAACGACAACATATGTACAATCCCTAGTTCGGGGTTCGAGTTCTCCTAG
 ATGTACAATCCCTAG
 ATGATAATTAGGCGTTCACGATACACAATGGAAGGAGAGGCGGGCCCTGCAGGCTAA
 ATGCGTACCTCGTAG
 ATGGAAGGAGAGGCGGGCCCTGCAGGCTAA
 ATGCACAAGTCGCTTGATATGGGGTGGTAG
 ⋮
 ATGCGCTAA
 ATGCTACCGGGTAGGGATAGCCCGATGGGGGGCATGGAC…CAGGGGCTGGACCCCGTTGCAAATAATTCCTCGAAATGA
 ATGGGGGGCATGGACTTAGGCGGCCCCAGCTTATTCTAC…CAGGGGCTGGACCCCGTTGCAAATAATTCCTCGAAATGA
 ATGGACTTAGGCGGCCCCAGCTTATTCTACCACCCCATA…CAGGGGCTGGACCCCGTTGCAAATAATTCCTCGAAATGA
 ATGGTTCTAATCTCGGGCAGCTACGAGGTACGCATGCAA…CAGGGGCTGGACCCCGTTGCAAATAATTCCTCGAAATGA
 ATGCAAAACCACTCCTCGATCTGTCAGGGGCTGGACCCCGTTGCAAATAATTCCTCGAAATGA
 ATGTTGTCGTTTCCCATTTTGTGTCCGATCGGACTATCGGAGTCTGCGGTCTAA
 ATGACTGTACTAGGTCACGGTCAATCCTAA
 ATGCCCCATACGTGA
 ATGAGCATGCGTCGGAAGCTTTGCTTACAACCGCGACAGAGATCAAGCAATTGA
 ATGCGTCGGAAGCTTTGCTTACAACCGCGACAGAGATCAAGCAATTGA
 ATGAAATATGAGACAGCTTCGGGACACTTGGAACCTTAT…CTGCTGGTGCTTCATTCCCATCTAGGAATCTGTTATTAG
 ATGAGACAGCTTCGGGACACTTGGAACCTTATCCTTACAATTGCAATGCGGTAG
 ATGCGGTAG
 ATGTGA

So I was curious whether the CUBs or EXPs measurements could be applied to the single CDS or the vector of CDSs. Either way, I was wondering if there is any chance to have CUBScout methods that leverage these dedicated data structures as they are optimized for the Bio ecosystem (I meant the BioSequences types by the way).

Best.

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