Biology is an interesting world and bioinformatic is where computer science meets biology,
Today I will describe a simple yet interesting bioinformatic problem from an algorithmic prospective.: Calculate the reverse complement of DNA bases using Javascript.

In this article, I am using a bioinformatic problem because is fun and interesting, but I will be mostly talking about JavaScript performance.
We will

• Start describing how DNA works (with some big simplifications… Eih! I am not a biologist!),
• Propose some implementations, and then
• try to archive the best time performance, comparing the time for completing the task.

heads-up: A basic knowledge of JavaScript language is required to follow along.

What’s the reverse complement?

Before explaining it, bear with me for a small tour of how DNA looks like.

Let start with some concepts,

The DNA helix is composed of two strands like in the image above.
A strand is a long sequence of this for letters ATGC ( each letter is a specific nucleotide Adenine, Thymidine, Guanidine, Cytidine ) in some order.
There is a specific relation between what is the first strand and what there is on the second strand: for each A in the first sequence there is a T on the other strand and vice versa, and for each G a C will be on the other strand.

The conversion from map DNA strand to complementary strang would be something like:

'A': 'T',
'G': 'C',
'T': 'A',
'C': 'G'

Here is an example:

I often hear these two sequences named 5’ to 3’’ ( 3’ end) and the second string is named 3’ to 5’ (5’’ end). The direction of reading is in both from 5’ to 3’’ and this means that a sequence is read from left to right but the other one (the complementary) is read from right to left.

In most of the file formats and web APIs that I worked with since the complementary DNA strand can be calculated from the first strand sequence, only one DNA strand is provided ( 3’ end) and is up to us to calculate the complementary.

Now, we have enough for our small challenge:

How can I generate a complementary strand?

Given an input:
TTATACGACTCACTATAGGGAGACTTAAGAAG
The expected output should look like this:
CTTCTTAAGTCTCCCTATAGTGAGTCGTATAA

Remember: we are reading the complementary in reverse order so the DNA sequence starts TT the complementary will end with AA.

Input:

TT ATACGACTCACTATAGGGAGACTTAAGAAG
Output:

CTTCTTAAGTCTCCCTATAGTGAGTCGTAT AA

Ok, let make the code talks for us:

Let start with a modern approach, a map

const map = (sequence) => {
    const map = {'A': 'T', 'T': 'A', 'G': 'C', 'C': 'G'}
    return sequence.split('').reverse().map(bp => map[bp]).join("")
}

This is “easy” to read and the steps are :

We take the input
“TACGA”
We separate each char and create an array
[ ‘T’ , ’A’ , ’C’ , ’G’ , ’A’]
Then map each char into his complementary
[ ‘A’ , ’T’ , ’G’ , ’C’ , ’T’]
We reverse
[ ‘T’ , ’C’ , ’G’ , ’T’ , ’A’]
And the join in a string
“TCGTA”

That’s it… right?

In most cases, yes, but today we are a bit more stubborn and we will try to find the best performance time for this job.
Why? Well even a small bacterial DNA can range in size anywhere from 130 kbp to over 14 Mbp ( a bp is a single letter/Nucleotide) so being fast could be important.

Ok, we have the rules, now let me present our players :

Player1:
We just saw the map implementation, let call map,

const map = (sequence) => {
    const map = {'A': 'T', 'T': 'A', 'G': 'C', 'C': 'G'}
    return sequence.split('')
                   .reverse()
                   .map(bp => map[bp])
                   .join("")
}

Player2: for loop and with if:

const forLoop = (sequence) => {
    let complement = ''
    for (let idx = 0; idx < sequence.length; idx++) {
        if (sequence[idx] === 'A') {
            complement = 'T' + complement
        } else if (sequence[idx] === 'T') {
            complement = 'A' + complement
        } else if (sequence[idx] === 'G') {
            complement = 'C' + complement
        } else if (sequence[idx] === 'C') {
            complement = 'G' + complement
        }
    }
    return complement
}

Player3: A for with a switch case:

const forSwitch = (sequence) => {
    let complement = '';

    for (let idx = 0, sL = sequence.length; idx < sL; idx++) {
        switch (sequence[idx]) {
            case 'A':
                complement = 'T' + complement
                break;
            case 'T':
                complement = 'A' + complement
                break;
            case 'G':
                complement = 'C' + complement
                break;
            case 'C':
                complement = 'G' + complement
                break;
        }
    }
    return complement
}

We will run these implementations ( and some small variations, github for more details ), 10000 times on a 35752 long DNA sequence and record the best time, the worst time, and the overall average time.

Ready go!

This graph is not that easy to read, let me provide a table ordered by

It looks like “replace with dictionary” is the worst in timing, and “optimized switch case” is the best.

Wrapping up,
In this implementation I can see that:

• The regular expression and the dictionary are slower than if and switch case
• For is the faster loop
• switch case wins on if else if
• The optimized of ‘for loop’ give some small improvements

Bonus, (what optimized for means):

Maybe you already noted the ‘switch case’ implementation. During my review of this topic, I fell on this website ( https://browserdiet.com/ ) and learned something interesting about the for loop that I didn’t know.

for ([initialization]; [condition]; [final-expression]){
        Statement
}

Every time a ‘statement’ gets executed the condition block runs again.
This sounds clear, but also sequence.length will re-calculate each interaction, consuming more time, and this is bad!

And there is a simple solution,

We can instance a variable with the value of sequence.length
in the initialization block:

for (let idx = 0; idx < sequence.length; idx++) {
    // sequence.length is calculated every interaction
}

for (let idx = 0, sL = sequence.length; idx < sL; idx++) {
    // sequence.length is calculated only 1 time
}

Thanks for taking the time to read this article and let me know any feedback, have a great day!

References:
https://en.wikipedia.org/wiki/Bacterial_genome
https://en.wikipedia.org/wiki/DNA
https://leanylabs.com/blog/js-forEach-map-reduce-vs-for-for_of/
DNA image from https://commons.wikimedia.org/wiki/File:0321_DNA_Macrostructure.jpg