Most efficient way to store a big DNA sequence?

Question

I want to pack a giant DNA sequence with an iOS app (about 3,000,000,000 base pairs). Each base pair can have a value A, C, T or G

Answer 1

If you don't mind having a complex solution, take a look at this paper or this paper or even this one which is more detailed.

But I think you need to specify better what you're dealing with. Some specifics applications can lead do diferent storage. For example, the last paper I cited deals with lossy compression of DNA...

Answer 2

Base pairs always pair up, so you should only have to store one side of the strand. Now, I doubt that this works if there are certain mutations in the DNA (like a di-Thiamine bond) that cause the opposite strand to not be the exact opposite of the stored strand. Beyond that, I don't think you have many options other than to compress it somehow. But, then again, I'm not a bioinformatics guy, so there might be some pretty sophisticated ways to store a bunch of DNA in a small space. Another idea if it's an iOS app is just putting a reader on the device and reading the sequence from a web service.

Answer 3

You can use the tools like MFCompress, Deliminate,Comrad.These tools provides entropy less than 2.That is for storing each symbol it will take less than 2 bits

Answer 4

I think you'll have to use two bits per base pair, plus implement compression as described in this paper.

"DNA sequences... are not random; they contain repeating sections, palindromes, and other features that could be represented by fewer bits than is required to spell out the complete sequence in binary...

With the proposed algorithm, sequence will be compressed by 75% irrespective of the number of repeated or non-repeated patterns within the sequence."

DNA Compression Using Hash Based Data Structure, International Journal of Information Technology and Knowledge Management July-December 2010, Volume 2, No. 2, pp. 383-386.

Edit: There is a program called GenCompress which claims to compress DNA sequences efficiently:

http://www1.spms.ntu.edu.sg/~chenxin/GenCompress/

Edit: See also this question on BioStar.

Answer 5

Use a diff from a reference genome. From the size (3Gbp) that you post, it looks like you want to include a full human sequences. Since sequences don't differ too much from person to person, you should be able to compress massively by storing only a diff.

Could help a lot. Unless your goal is to store the reference sequence itself. Then you're stuck.

Answer 6

You want to look into a 3d space-filling curve. A 3d sfc reduces the 3d complexity to a 1d complexity. It's a little bit like n octree or a r-tree. If you can store your full dna in a sfc you can look for similar tiles in the tree although a sfc is most likely to use with lossy compression. Maybe you can use a block-sorting algorithm like the bwt if you know the size of the tiles and then try an entropy compression like a huffman compression or a golomb code?