# Optimizing dinucleotides count in a DNA sequence type \`LongDNA\`

**URL:** <https://discourse.julialang.org/t/optimizing-dinucleotides-count-in-a-dna-sequence-type-longdna/101583>\
**Category:** Performance\
**Tags:** question, performance, strings, biology\
**Created:** [July 13, 2023, 4:51pm UTC](https://discourse.julialang.org/t/optimizing-dinucleotides-count-in-a-dna-sequence-type-longdna/101583 "2023-07-13T16:51:55Z")\
**Posts on this page:** 2\
**Page:** 2

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**Author:** ![Dan](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/dan/32/42581_2.png) [@Dan](https://discourse.julialang.org/u/Dan)\
**Post date:** [July 15, 2023, 9:00pm UTC](https://discourse.julialang.org/t/optimizing-dinucleotides-count-in-a-dna-sequence-type-longdna/101583/21 "2023-07-15T21:00:01Z")

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This looks like a problem which would use SIMD for an optimal solution. Perhaps the only way to get Julia to use SIMD effectively in this problem is hand-crafted code.

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<div class="post-metadata">

**Author:** ![rocco\_sprmnt21](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/rocco_sprmnt21/32/20127_2.png) [@rocco\_sprmnt21](https://discourse.julialang.org/u/rocco_sprmnt21)\
**Post date:** [July 17, 2023, 5:33pm UTC](https://discourse.julialang.org/t/optimizing-dinucleotides-count-in-a-dna-sequence-type-longdna/101583/23 "2023-07-17T17:33:43Z")

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Trying to understand how some of the internals of the decode and encode functions work, I discovered the ‘data’ property of DNA sequences.  
Using this property, execution times can be shortened.  
julia\> using BioSequences, BenchmarkTools,StatsBase

```julia
julia> rseq = randdnaseq(10^6)
1000000nt DNA Sequence:
AACATCACCCGTGCCAATTACACGTCGTCCTTATTATAA…GAAAGCCATGCAGAAATTTTACACAGATCAAACTTCTCT

julia> function countdin(rseq)
    h1=countmap(reinterpret(reshape,UInt8,rseq.data))
    lseq=LongSequence{DNAAlphabet{4}}(undef, rseq.len-2)
    copyto!(lseq, 1, rseq, 2, rseq.len-2)
    h2=countmap(reinterpret(reshape,UInt8,lseq.data))
    fdict=mergewith(+,h1,h2)
    res=Dict{Tuple{DNA,DNA},Int}()
    for x in keys(fdict)
        c=x==0 ? continue : reinterpret.(DNA, ((x<<4)>>4, x>>4))  
        res[c]=fdict[x]
    end
    res
end
countdin (generic function with 1 method)

julia> @btime countdin(rseq)
  986.100 μs (30 allocations: 497.28 KiB)
Dict{Tuple{DNA, DNA}, Int64} with 16 entries:
  (DNA_G, DNA_T) => 62503
  (DNA_T, DNA_A) => 62252
  (DNA_G, DNA_C) => 62576
  (DNA_C, DNA_T) => 62250
  (DNA_A, DNA_A) => 62555
  (DNA_C, DNA_C) => 62272
  (DNA_G, DNA_G) => 62520
  (DNA_C, DNA_G) => 62609
  (DNA_T, DNA_T) => 62469
  (DNA_T, DNA_C) => 62567
  (DNA_A, DNA_T) => 62622
  (DNA_A, DNA_C) => 62414
  (DNA_T, DNA_G) => 62555
  ⋮ => ⋮

```

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