AminoSee DNA Viewer

by Tom Atkinson

Easy install

git clone https://github.com/tomachinz/AminoSee ; cd AminoiSee ; npm install ; ./installer.sh ; aminosee dna/* ; aminosee --test

Convert large ascii-triplet DNA files into png images. 25 unique colour hues represent the 4 start/stop codons plus the 21 Amino acids. Supports any ASCII text based genome such as FASTA, GBK, .txt, .gff etc, if it has text like GTAGCCTAGTCGATTCAG or maybe UUGCUTGUTGUTGUTGTUCUT then AminoSee can render up a set of images of it! The triplet for Lyson AAA would render to this indigo colour at 313

A node command to convert any DNA sequence into an abstract image, and a built-in web server to show your work to others. Your renders will end up in ~/AminoSee_Output or create a folder with that name in the same folder as your DNA to enable zero-conf cluster rendering (it uses lock files to synchronise the nodes).

Tested with FASTA .fa and GBK files on macOS, Linux and Windows. Just feed it a file, simple as:

aminosee dna/megabase.fa

To render the sample DNA included in this repo. The colours used are:

The Colour Lookup Table

**Amino Acids**  **Hue°**	**RGB*     **Count**     **Description**
Amber	        47°   255,227,128       666,921   STOP CODONS
Tryptophan    188°  128,238,255       893,683   Group I: Nonpolar amino acids
Methionine    110°  149,255,128       944,572   START Codon
Opal          240°  128,128,255       991,394   STOP Codon
Ochre         0°    255,128,128     1,046,848	  STOP Codon Mystery_chrX Ochre
Aspartic acid 31°   255,193,128     1,148,847	  Group III: Acidic amino acids
Histidine     329°  255,128,193     1,658,210	  Group IV: Basic amino acids
Tyrosine      282°  217,128,255     1,693,723   Group II: Polar, uncharged amino acids
Cysteine      63°   249,255,128     1,713,072   Group II: Polar, uncharged amino acids  
Glutamic acid 16°   255,162,128     1,812,490	  Group III: Acidic amino acids
Glutamine     250°  149,128,255     1,912,419	  Group II: Polar, uncharged amino acids    
Alanine       94°   183,255,128     1,942,961	  Group I: Nonpolar amino acids  
Asparagine    266°  183,128,255     2,053,997	  Group II: Polar, uncharged amino acids  
Arginine      297°  249,128,255     2,357,076	  Group IV: Basic amino acids    
Proline       344°  255,128,162     2,379,170	  Group I: Nonpolar amino acids    
Glycine       78°   217,255,128     2,411,578	  Group I: Nonpolar amino acids    
Valine        125°  128,255,138     2,503,263	  Group I: Nonpolar amino acids  
Threonine     219°  128,172,255     2,513,447	  Group II: Polar, uncharged amino acids
Lysine        313°  255,128,227     2,966,509	  Group IV: Basic amino acids
Phenylalanine 172°  128,255,238     3,020,290	  Group I: Nonpolar amino acids
Isoleucine    157°  128,255,206     3,097,667	  Group I: Nonpolar amino acids  
Serine        203°  128,206,255     4,389,976	  Group II: Polar, uncharged amino acids
Leucine       141°  128,255,172     5,447,658	  Group I: Nonpolar amino acids

No file size limit - tested with a 3.11 GB Chimpanzee genome - AminoSee streams through the file - one line at a time - and outputs a pixel of colour for each triplet found. AminoSee makes an estimate of how many amino acids are present, and starts blending for example 100 codons per pixel in a 9 megapixels image. Smaller microbes and the C.Elegans worm can be seen at 1 pixel per codon resolution on a large 4k monitor! I get about 2 MB/s on my 2015 Mac. To remove the limit use --maxpix 69000000 but I think you will find the default of 9 megapixels is fine.

What can I see?

DNA structures like repeats, genes, chromosomes, centromere, telomeres etc - which otherwise would appear as incredibly thin 1-pixel-thick lines.

Why on Earth?

I got the idea while looking at raw DNA and pondering if that advent of 4K monitors mite allow me to "See" all the information. In particular, I'm interested in seeing if it could be useful for cross-species comparisons, criminal forensics, visualisation and animation of mutations over time.

It is possible to see large chromosomal structures such as the Telomeres (grip points at the endings), the Centromeres (place in middle where chromosome breaks in two), and generally check how different the species look.

And the real reason?

I was wondering how to prove or disprove the official Sumerian account of human history. The hypothesis being that if the Annunaki had spent tens of thousands of years meddling with our DNA, perhaps this will show up visually compared to the natural mutations of ~6 million years which is the separation from homo sapiens to a common Chimp ancestor AFAIK. If the story is true, it might be possible to see something happening around 340,000 to 450,000 years ago, I'm focussing on the fused chromosome 2-pq in humans which is normally 2p and 2q in other apes; and the Y chromosome for its slow rate of mutation to begin with.

Among the living primates, Humans are most closely related to the apes, which include the lesser apes (Gibbon) and the great apes (Chimpanzee, Gorilla and Orangutan). These so-called hominoids — that is, the gibbons, great apes and humans — emerged and diversified during the Miocene epoch, approximately 23 million to 5 million years ago. The last common ancestor that humans had with chimpanzees lived about 6 million to 7 million years ago. Source: https://www.scientificamerican.com/article/fossil-reveals-what-last-common-ancestor-of-humans-and-apes-looked-liked/

How on earth is it done?

It creates full colour images and was designed to enable inter-species comparisons by enabling a visual diff; to understand the role of the regulatory “non-coding” junk DNA; as a thought experiment and exercise in processing enormous datasets; but most of all just purely out of curiosity and to inspire youth to get into science. A new way to view DNA data which maps a spectrum of colour hues to each amino acid, encoding all the information visually. It can take an infinite file size as input, and crunch this into a linear render (left to right, top to bottom), and also a space filling Hilbert curve (top left to centre to top right via all corners).

3D and 2D Hilbert mapping

An experimental 3D mode enables visitors to http://aminosee.funk.nz/ to interactively fly through the DNA using the keyboard and mouse for a closer look! This even works on modern mobiles, but a desktop computer running macOS, Windows, or Linux is suggested. You can currently browse though his renderings in the /output/ folder where there is of a handful of organisms such a human, primates, Octopus, Eucalyptus, Cannabis, Alligator, and the Brown Kiwi, with more coming soon, my computer is not powerful enough.

I'm about to get in touch with some universities and genomics researchers worldwide, once the code has settled down a bit, hoping to gain some feedback and suggestions on the final colours for each amino acid, which I am still open to, and planning a way to customise it.

Motto: “I can see it now - I can AminoSee it!”

Amino.See.No.Evil (AminoSee) is a DNA visualisation written in NodeJS, ThreeJS and Carlo. It does this with a terminal command and batch scripts that can be run (such as batch-peptides.sh in ./dna), Its been tested with Fasta or GBK files I downloaded. AminoSee assigns a unique colour hue to each amino acid and start/stop codon,

This is done to enhance the visual prominence of genetic structures -

The bunching of the curve preserves local sequence proximity such that 90% of the DNA that is close to its neighbour - such as genes - are also close in proximity in the image - even at different resolutions, which is almost impossible when converted 1D into higher dimensions. Genomics researchers can convert any file containing ASCII blocks of DNA (tested with popular formats Fasta, GBK, and also just .txt) into an image. A unique visualisation of DNA / RNA residing in text files, AminoSee is a way to render arbitrarily large files - due to support for streamed processing - into a static size PNG image. Special thanks and shot-outs to David Hilbert who invented it in 1891! Computation is done locally, and the files do not leave your machine. A back-end terminal daemon cli command that can be automated by scripts in /dna/ folder is soon to be enhanced with a front-end GUI. AminoSee features asynchronous streaming processing enabling arbitrary size files to be processed. It has been tested with files in excess of 4 GB and does not need the whole file in memory at any time. The dna/batch-peptides.sh script is currently required for bulk rendering. Alternatively use the GUI to Drag and drop files to render a unique colour view of RNA or DNA stored in text files, output to PNG graphics file, then launches an WebGL browser that projects the image onto a 3D Hilbert curve for immersive viewing, using THREEjs. Command line options allow one to filter by peptide.

"description": "Allows genomics researchers to convert any file containing ASCII blocks of DNA (Fasta, GBK, .txt) into an image. A unique visualisation of DNA / RNA residing in text files, AminoSee is a way to render arbitrarily large files - due to support for streamed processing - into a static size PNG image using a pseudo-Hilbert infinite space filling curve written in the 18th century! Computation is done locally, and the files do not leave your machine. A back-end terminal daemon cli command that can be scripted is combined with a front-end GUI in Carlo, AminoSee features asynchronous streaming processing enabling arbitrary size files to be processed. It has been tested with files in excess of 4 GB and does not need the whole file in memory at any time. In a directory with DNA files try running aminosee *. Alternatively use the GUI to Drag and drop files to render a unique colour view of RNA or DNA stored in text files, output to PNG graphics file, then launches an WebGL browser that projects the image onto a 3D