If you have ever read a research paper on genomics and wondered what that mesmerising circular diagram is — the one that looks like someone wrapped a London Tube map around a pie chart — you have met a Circos PNG. It looks complicated, and in a way it is. But once you understand what it is doing, it becomes one of the clearest ways to show complex data ever invented.
This article covers everything you need to know: what Circos is, what a PNG output means in this context, how the tool works, where it is used, and why so many scientists (and non-scientists) reach for it when they need to make data beautiful.
What is Circos?
Circos is an open-source data visualisation software created by Martin Krzywinski at Canada's Michael Smith Genome Sciences Centre. It was officially published in 2009 in Genome Research, one of the most respected journals in the field, and has been widely cited ever since.
The word "Circos" comes from the circular layout it uses. Instead of plotting data in straight lines or on a flat grid, Circos arranges it around a circle. Chromosomes (or any data segments) sit around the outer ring like the hours of a clock, and relationships between them are drawn as ribbons through the middle. Think of it as data that decided it was tired of being a boring bar chart and went full abstract art — except it still means something rigorous and scientific.
Circos runs on Perl and works on Windows, Mac, and Linux. It reads plain-text configuration files and data inputs to produce its output. That output comes in two formats: PNG and SVG. The PNG is the bitmap version — a raster image made of pixels — while the SVG is a vector version that scales without quality loss. Most publications and reports use the PNG because it is universal, easy to embed, and ready to share.
What Exactly is a Circos PNG?
A Circos PNG is the final image file that Circos generates after processing your data and configuration files. It is a standard PNG (Portable Network Graphics) file — the same format you use for screenshots, website images, and that meme you sent to a group chat last Tuesday.
What makes a Circos PNG different from just any PNG is what is inside it. Circos produces bitmap output in either 8-bit or 24-bit colour depth, configurable by the user. The resolution, dimensions, and exact visual layout of the image are all set in the tool's configuration files, giving researchers precise control over every element.
When Circos finishes rendering, it writes a file typically called circos.png to your working directory. The file size varies depending on complexity and resolution, but a standard plot might land around 300–500 KB — compact enough to drop into a paper or presentation without any drama.
"Circos makes no assumptions about your data, uses extremely simple input data format, and makes image creation and customisation easy." — Martin Krzywinski, circos.ca
How Does Circos Work?
Circos is driven by plain-text configuration files and GFF-style data files. You tell it what data you have, how you want each element to look, and which tracks to add. Circos then processes everything and draws the image from the outside in, layer by layer.
The Basic Components
Every Circos PNG starts with a karyotype file. This defines the segments — usually chromosomes — that sit around the outer ring of the circle. Each segment gets a name, a size (in base pairs for genomic data), and a colour.
Inside the ring, you can add multiple data tracks. A track is a visual layer that maps data values onto positions within each segment. Circos supports scatter plots, line plots, histograms, heat maps, tiles, text labels, and connectors. You can stack as many tracks as you need, working from the outer edge inward.
The most iconic feature is the ribbon links that cross through the middle. A link connects two positions — one on one chromosome, one on another — and the width of each ribbon end encodes the size of the relationship. This is where Circos really earns its reputation. Showing all genomic rearrangements in a cancer genome as crossing ribbons in one image is not just informative — it is genuinely striking.
Output: PNG vs SVG
| Format | Type | Best Used For | Scalability |
|---|---|---|---|
| PNG | Bitmap (raster) | Publications, web, presentations | Fixed resolution |
| SVG | Vector | Editable graphics, large-format print | Infinitely scalable |
The PNG is faster to produce and universally readable. The SVG allows post-processing in tools like Adobe Illustrator or Inkscape. For most everyday scientific publishing, the Circos PNG is the go-to choice — hence why it has its own dedicated tutorial section on the official Circos site.
Where is Circos PNG Used?
Circos started as a genomics tool, but it has grown well beyond that. Its circular layout works for any dataset that involves relationships between two or more things. That is a surprisingly wide category.
Genomics and Cancer Research
This remains the primary home of Circos PNG images. Researchers use them to show chromosome rearrangements, gene fusions, copy number variations, and single-nucleotide polymorphisms (SNPs). Circos has appeared on the covers of both Nature and Science — the two most prestigious journals in all of science — which tells you everything about the visual impact of these outputs.
Cancer genome projects in particular rely heavily on Circos PNG outputs. The COSMIC database (Catalogue of Somatic Mutations in Cancer) uses them to display how cancer genomes differ from healthy ones. When you see that striking circular image in a cancer research paper, there is a good chance it is a Circos PNG.
Beyond Genomics
Because Circos is data-agnostic, researchers have used it for a wide range of non-biological applications. Circos images have appeared in the New York Times (to visualise the 2008 US presidential debates), in studies tracking migration patterns between countries, and in analyses of trade flows, customer purchase trends, and courier shipment data. The circular form works wherever you have flow or relationships between categories — which turns out to be almost everywhere.
PNG vs SVG: Why Researchers Usually Choose PNG
The short answer: PNG just works everywhere. Email it, post it, embed it in a Word document, drop it into a slide deck. Nobody has to install anything special to open it. SVG, while technically superior for scalability and editability, requires vector software and can cause headaches in standard document workflows.
There is a practical trade-off, though. A Circos PNG at a fixed resolution looks sharp on screen and in print up to a certain size. If your journal asks for figures at 600 DPI, you need to configure Circos to render the PNG at that resolution upfront — unlike SVG, you cannot simply enlarge a PNG after the fact without losing quality.
Circoletto, a tool that layers BLAST sequence similarity searches on top of Circos, puts it plainly: users can choose between a "fast, lightweight, lower quality PNG" and the SVG for more demanding uses. In practice, most users start with the PNG and switch to SVG only when they need to make editorial changes or produce extremely large prints.
How to Generate a Circos PNG
Getting a Circos PNG out of raw data involves a few steps, but the overall process is more approachable than it might look from the outside. Here is the broad workflow:
1. Install Circos — Circos runs on Perl and is available under the GNU General Public License (GPL) v3. You can download it from circos.ca. It runs on Linux, Mac, and Windows.
2. Prepare your karyotype file — This defines your segments (chromosomes or any named categories). Several pre-built karyotype files for common model organisms are available in the Circos distribution.
3. Prepare your data files — Circos uses GFF-style data files (chromosome, start, end, value). These can be exported from bioinformatics pipelines, databases, or even custom scripts.
4. Write your configuration file — The circos.conf file tells Circos what to draw and how. This is where you define tracks, link files, colours, fonts, and image size.
5. Run Circos — A single command (circos in your terminal) processes everything and writes your PNG to the output directory. The process typically takes a few seconds to a couple of minutes depending on data complexity.
Why Circos PNG Matters for Scientific Communication
Science has a communication problem. The data keeps getting bigger, more layered, and more interconnected — and flat bar charts are struggling to keep up. A Circos PNG does not just display data; it helps researchers and readers see the structure of data at a glance.
Martin Krzywinski put it well when he noted that the goal of Circos was not just to create another charting tool but to make data look beautiful. That sounds like an aesthetic indulgence, but it is actually a practical one. Figures that are visually engaging get looked at longer. They get remembered. They get cited. In an era of information overload, a striking Circos PNG in a paper's abstract figure can be the difference between a reader engaging with the work or scrolling past.
Circos images have appeared in publications as varied as Wired, the New York Times, Condé Nast Portfolio, and American Scientist — not just academic journals. That kind of crossover rarely happens with genomics figures. Circos earned it by making science look like art without sacrificing the science.
Tools Built on Circos
Since its release, Circos has inspired a growing ecosystem of tools. Here is a quick overview of the main ones:
RCircos and circlize — R packages that let you create Circos-style plots within the R environment. Great for researchers already working in R for their statistical analysis.
NG-Circos — A JavaScript-based reimagining of Circos that supports interactive plots in web browsers. It offers 21 functional modules and allows users to hover over and click on data points, something the original Circos PNG cannot do.
CIRCUS — An R wrapper specifically for displaying structural genome variations from next-generation sequencing data. It simplifies the configuration process for non-bioinformaticians.
pyCirclize — A Python package for creating circular visualisations including Circos plots, chord diagrams, and radar charts. Built on matplotlib, it is accessible to anyone comfortable with Python.
CGDV — A web-based tool that wraps Circos to handle genomics and transcriptomics data automatically, generating output in both SVG and PNG formats without requiring users to write configuration files manually.
Common Mistakes When Working with Circos PNG
If you are new to Circos, a few traps tend to catch people out.
Setting the resolution too low. If you plan to use your Circos PNG in a publication, check your journal's requirements before you generate the image. Most journals want figures at 300–600 DPI. Configure the image dimensions and DPI in your circos.conf file before running — not after.
Overloading the image with tracks. Circos can technically handle dozens of tracks, but human eyes cannot. A Circos PNG with too many overlapping data layers becomes unreadable quickly. Start minimal and add tracks one at a time.
Ignoring the colour palette. Colour carries meaning in Circos. Poor colour choices make relationships hard to distinguish and undermine the whole point of the visualisation. Circos supports Brewer palettes — a set of colour schemes designed specifically for data visualisation — and using them is strongly recommended.
Forgetting to cite. If you use Circos in a publication, the developers ask that you cite the original 2009 Genome Research paper: Krzywinski, M. et al. Circos: an Information Aesthetic for Comparative Genomics. Genome Res (2009) 19:1639–1645.
Final Thoughts
A Circos PNG is more than a file format. It represents a whole approach to scientific communication — one that takes seriously the idea that how you present data shapes how it is understood. Developed by a scientist who was as interested in design as in biology, Circos has spent over a decade showing up in the world's top journals, newspapers, and magazines because it succeeds at something genuinely difficult: making complex, multi-layered, interconnected data instantly comprehensible.
Whether you are mapping cancer genomes, visualising migration flows, or just curious about what those beautiful circular diagrams in science papers actually are — now you know. It is a Circos PNG. And it earns every pixel.
Sources & References
- Krzywinski, M. et al. Circos: an Information Aesthetic for Comparative Genomics. Genome Research (2009) 19:1639–1645. PMC2752132
- Circos official documentation and introduction. circos.ca
- Cui, Y. et al. NG-Circos: next-generation Circos for data visualization and interpretation. NAR Genomics and Bioinformatics (2020) 2(3). Oxford Academic
- Genome Sciences Centre, BC Cancer Research. bcgsc.ca
- Galaxy Training Network. Visualisation with Circos. Galaxy Training Materials
- Darzentas, N. Circoletto: visualizing sequence similarity with Circos. Bioinformatics (2010) 26(20):2620–2621. Oxford Academic
- Novogene. Four Online Tools for Genomic Analysis and Visualization: Circos. novogene.com
- Nattestad, M. Making genomic data come alive with Circos plots. Medium (2025). Medium
If you have ever read a research paper on genomics and wondered what that mesmerising circular diagram is — the one that looks like someone wrapped a London Tube map around a pie chart — you have met a Circos PNG. It looks complicated, and in a way it is. But once you understand what it is doing, it becomes one of the clearest ways to show complex data ever invented.
This article covers everything you need to know: what Circos is, what a PNG output means in this context, how the tool works, where it is used, and why so many scientists (and non-scientists) reach for it when they need to make data beautiful.
What is Circos?
Circos is an open-source data visualisation software created by Martin Krzywinski at Canada's Michael Smith Genome Sciences Centre. It was officially published in 2009 in Genome Research, one of the most respected journals in the field, and has been widely cited ever since.
The word "Circos" comes from the circular layout it uses. Instead of plotting data in straight lines or on a flat grid, Circos arranges it around a circle. Chromosomes (or any data segments) sit around the outer ring like the hours of a clock, and relationships between them are drawn as ribbons through the middle. Think of it as data that decided it was tired of being a boring bar chart and went full abstract art — except it still means something rigorous and scientific.
Circos runs on Perl and works on Windows, Mac, and Linux. It reads plain-text configuration files and data inputs to produce its output. That output comes in two formats: PNG and SVG. The PNG is the bitmap version — a raster image made of pixels — while the SVG is a vector version that scales without quality loss. Most publications and reports use the PNG because it is universal, easy to embed, and ready to share.
What Exactly is a Circos PNG?
A Circos PNG is the final image file that Circos generates after processing your data and configuration files. It is a standard PNG (Portable Network Graphics) file — the same format you use for screenshots, website images, and that meme you sent to a group chat last Tuesday.
What makes a Circos PNG different from just any PNG is what is inside it. Circos produces bitmap output in either 8-bit or 24-bit colour depth, configurable by the user. The resolution, dimensions, and exact visual layout of the image are all set in the tool's configuration files, giving researchers precise control over every element.
When Circos finishes rendering, it writes a file typically called circos.png to your working directory. The file size varies depending on complexity and resolution, but a standard plot might land around 300–500 KB — compact enough to drop into a paper or presentation without any drama.
"Circos makes no assumptions about your data, uses extremely simple input data format, and makes image creation and customisation easy." — Martin Krzywinski, circos.ca
How Does Circos Work?
Circos is driven by plain-text configuration files and GFF-style data files. You tell it what data you have, how you want each element to look, and which tracks to add. Circos then processes everything and draws the image from the outside in, layer by layer.
The Basic Components
Every Circos PNG starts with a karyotype file. This defines the segments — usually chromosomes — that sit around the outer ring of the circle. Each segment gets a name, a size (in base pairs for genomic data), and a colour.
Inside the ring, you can add multiple data tracks. A track is a visual layer that maps data values onto positions within each segment. Circos supports scatter plots, line plots, histograms, heat maps, tiles, text labels, and connectors. You can stack as many tracks as you need, working from the outer edge inward.
The most iconic feature is the ribbon links that cross through the middle. A link connects two positions — one on one chromosome, one on another — and the width of each ribbon end encodes the size of the relationship. This is where Circos really earns its reputation. Showing all genomic rearrangements in a cancer genome as crossing ribbons in one image is not just informative — it is genuinely striking.
Output: PNG vs SVG
| Format | Type | Best Used For | Scalability |
|---|---|---|---|
| PNG | Bitmap (raster) | Publications, web, presentations | Fixed resolution |
| SVG | Vector | Editable graphics, large-format print | Infinitely scalable |
The PNG is faster to produce and universally readable. The SVG allows post-processing in tools like Adobe Illustrator or Inkscape. For most everyday scientific publishing, the Circos PNG is the go-to choice — hence why it has its own dedicated tutorial section on the official Circos site.
Where is Circos PNG Used?
Circos started as a genomics tool, but it has grown well beyond that. Its circular layout works for any dataset that involves relationships between two or more things. That is a surprisingly wide category.
Genomics and Cancer Research
This remains the primary home of Circos PNG images. Researchers use them to show chromosome rearrangements, gene fusions, copy number variations, and single-nucleotide polymorphisms (SNPs). Circos has appeared on the covers of both Nature and Science — the two most prestigious journals in all of science — which tells you everything about the visual impact of these outputs.
Cancer genome projects in particular rely heavily on Circos PNG outputs. The COSMIC database (Catalogue of Somatic Mutations in Cancer) uses them to display how cancer genomes differ from healthy ones. When you see that striking circular image in a cancer research paper, there is a good chance it is a Circos PNG.
Beyond Genomics
Because Circos is data-agnostic, researchers have used it for a wide range of non-biological applications. Circos images have appeared in the New York Times (to visualise the 2008 US presidential debates), in studies tracking migration patterns between countries, and in analyses of trade flows, customer purchase trends, and courier shipment data. The circular form works wherever you have flow or relationships between categories — which turns out to be almost everywhere.
PNG vs SVG: Why Researchers Usually Choose PNG
The short answer: PNG just works everywhere. Email it, post it, embed it in a Word document, drop it into a slide deck. Nobody has to install anything special to open it. SVG, while technically superior for scalability and editability, requires vector software and can cause headaches in standard document workflows.
There is a practical trade-off, though. A Circos PNG at a fixed resolution looks sharp on screen and in print up to a certain size. If your journal asks for figures at 600 DPI, you need to configure Circos to render the PNG at that resolution upfront — unlike SVG, you cannot simply enlarge a PNG after the fact without losing quality.
Circoletto, a tool that layers BLAST sequence similarity searches on top of Circos, puts it plainly: users can choose between a "fast, lightweight, lower quality PNG" and the SVG for more demanding uses. In practice, most users start with the PNG and switch to SVG only when they need to make editorial changes or produce extremely large prints.
How to Generate a Circos PNG
Getting a Circos PNG out of raw data involves a few steps, but the overall process is more approachable than it might look from the outside. Here is the broad workflow:
1. Install Circos — Circos runs on Perl and is available under the GNU General Public License (GPL) v3. You can download it from circos.ca. It runs on Linux, Mac, and Windows.
2. Prepare your karyotype file — This defines your segments (chromosomes or any named categories). Several pre-built karyotype files for common model organisms are available in the Circos distribution.
3. Prepare your data files — Circos uses GFF-style data files (chromosome, start, end, value). These can be exported from bioinformatics pipelines, databases, or even custom scripts.
4. Write your configuration file — The circos.conf file tells Circos what to draw and how. This is where you define tracks, link files, colours, fonts, and image size.
5. Run Circos — A single command (circos in your terminal) processes everything and writes your PNG to the output directory. The process typically takes a few seconds to a couple of minutes depending on data complexity.
Why Circos PNG Matters for Scientific Communication
Science has a communication problem. The data keeps getting bigger, more layered, and more interconnected — and flat bar charts are struggling to keep up. A Circos PNG does not just display data; it helps researchers and readers see the structure of data at a glance.
Martin Krzywinski put it well when he noted that the goal of Circos was not just to create another charting tool but to make data look beautiful. That sounds like an aesthetic indulgence, but it is actually a practical one. Figures that are visually engaging get looked at longer. They get remembered. They get cited. In an era of information overload, a striking Circos PNG in a paper's abstract figure can be the difference between a reader engaging with the work or scrolling past.
Circos images have appeared in publications as varied as Wired, the New York Times, Condé Nast Portfolio, and American Scientist — not just academic journals. That kind of crossover rarely happens with genomics figures. Circos earned it by making science look like art without sacrificing the science.
Tools Built on Circos
Since its release, Circos has inspired a growing ecosystem of tools. Here is a quick overview of the main ones:
RCircos and circlize — R packages that let you create Circos-style plots within the R environment. Great for researchers already working in R for their statistical analysis.
NG-Circos — A JavaScript-based reimagining of Circos that supports interactive plots in web browsers. It offers 21 functional modules and allows users to hover over and click on data points, something the original Circos PNG cannot do.
CIRCUS — An R wrapper specifically for displaying structural genome variations from next-generation sequencing data. It simplifies the configuration process for non-bioinformaticians.
pyCirclize — A Python package for creating circular visualisations including Circos plots, chord diagrams, and radar charts. Built on matplotlib, it is accessible to anyone comfortable with Python.
CGDV — A web-based tool that wraps Circos to handle genomics and transcriptomics data automatically, generating output in both SVG and PNG formats without requiring users to write configuration files manually.
Common Mistakes When Working with Circos PNG
If you are new to Circos, a few traps tend to catch people out.
Setting the resolution too low. If you plan to use your Circos PNG in a publication, check your journal's requirements before you generate the image. Most journals want figures at 300–600 DPI. Configure the image dimensions and DPI in your circos.conf file before running — not after.
Overloading the image with tracks. Circos can technically handle dozens of tracks, but human eyes cannot. A Circos PNG with too many overlapping data layers becomes unreadable quickly. Start minimal and add tracks one at a time.
Ignoring the colour palette. Colour carries meaning in Circos. Poor colour choices make relationships hard to distinguish and undermine the whole point of the visualisation. Circos supports Brewer palettes — a set of colour schemes designed specifically for data visualisation — and using them is strongly recommended.
Forgetting to cite. If you use Circos in a publication, the developers ask that you cite the original 2009 Genome Research paper: Krzywinski, M. et al. Circos: an Information Aesthetic for Comparative Genomics. Genome Res (2009) 19:1639–1645.
Final Thoughts
A Circos PNG is more than a file format. It represents a whole approach to scientific communication — one that takes seriously the idea that how you present data shapes how it is understood. Developed by a scientist who was as interested in design as in biology, Circos has spent over a decade showing up in the world's top journals, newspapers, and magazines because it succeeds at something genuinely difficult: making complex, multi-layered, interconnected data instantly comprehensible.
Whether you are mapping cancer genomes, visualising migration flows, or just curious about what those beautiful circular diagrams in science papers actually are — now you know. It is a Circos PNG. And it earns every pixel.
Sources & References
- Krzywinski, M. et al. Circos: an Information Aesthetic for Comparative Genomics. Genome Research (2009) 19:1639–1645. PMC2752132
- Circos official documentation and introduction. circos.ca
- Cui, Y. et al. NG-Circos: next-generation Circos for data visualization and interpretation. NAR Genomics and Bioinformatics (2020) 2(3). Oxford Academic
- Genome Sciences Centre, BC Cancer Research. bcgsc.ca
- Galaxy Training Network. Visualisation with Circos. Galaxy Training Materials
- Darzentas, N. Circoletto: visualizing sequence similarity with Circos. Bioinformatics (2010) 26(20):2620–2621. Oxford Academic
- Novogene. Four Online Tools for Genomic Analysis and Visualization: Circos. novogene.com
- Nattestad, M. Making genomic data come alive with Circos plots. Medium (2025). Medium
