You might learn a lot about that house—the rooms, the doors, the furniture—but you would miss the bigger story: the streets, the neighborhoods, and all the ways the city changes from one place to another.

Something similar happens when scientists study bacterial genomes one at a time.

Over the past decade, researchers have collected thousands of bacterial genomes. These genomes contain an enormous amount of information about how bacteria survive, adapt, and evolve. But comparing thousands of individual genomes can quickly become a computational maze.

That is where PANORAMA enters the story.

Developed by Jérôme Arnoux and colleagues, PANORAMA is a computational tool designed to explore bacterial pangenomes—the complete collection of genetic possibilities found across a species or group of related organisms. Instead of looking at every genome as an isolated object, the approach represents their shared and variable genetic features as a graph.

Think of this graph as a giant subway map.

Some stations appear on almost every route. These represent genes that are highly conserved. Other stations appear only on certain routes, representing genes that some bacteria possess while others do not. By looking at the entire network, scientists can begin to see not just *what genes exist*, but how they are organized and how biological systems are distributed across populations.

The researchers put PANORAMA to the test using 941 genomes of Pseudomonas aeruginosa, a bacterium important in human health. They used the tool to investigate biological systems, including bacterial defense mechanisms against viruses known as bacteriophages. They then expanded the analysis to more than 6,000 genomes from four Enterobacteriaceae species.

The result is more than a faster way to process data.

PANORAMA allows researchers to ask a bigger question: What can an entire microbial species do, genetically speaking?

By comparing pangenomes, the researchers could identify systems shared between species as well as distinctive features. They could also find recurring genomic locations where genetic material is inserted—clues that may reveal common evolutionary processes.

And this is perhaps the most exciting part of the story.

Every bacterial genome is like a page in a huge evolutionary book. Until recently, reading thousands of those pages together was difficult. PANORAMA provides a way to turn those pages into a map, allowing scientists to see patterns that might disappear when each genome is studied separately.

The study, published in PLOS Computational Biology in July 2026, presents PANORAMA as a foundation for large-scale comparative pangenomics. The software and accompanying analysis resources are openly available, giving other researchers the opportunity to explore microbial diversity themselves.

So the story is not really about one bacterium or one genome.

It is about changing the way we look at life.

Instead of asking, “What is inside this genome?”, scientists can increasingly ask, “What is the full genetic landscape of this species—and how did it become this way?”

And sometimes, when you stop looking at one house and finally see the whole city, the most interesting discoveries are hiding in the streets between them.

Read more at https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1013856

A recent study by Webster and Chapman introduces Buscogeny (https://github.com/Jwebster89/Buscogeny), an open-source bioinformatics pipeline designed to make this process easier. The tool uses BUSCO (Benchmarking Universal Single-Copy Orthologs), which identifies conserved genes that are expected to occur as single copies in particular groups of organisms. These genes act like evolutionary landmarks, allowing researchers to compare genomes and investigate their relationships.

Buscogeny brings several steps of phylogenomic analysis into one workflow. It identifies BUSCO genes, extracts and aligns their sequences, removes unreliable regions, combines information from multiple genes, and uses the resulting data to construct a phylogenetic tree. It also provides quality-control information, helping researchers identify genomes that may be too incomplete for reliable analysis.

The authors demonstrate the usefulness of Buscogeny with bacterial and fungal genomes, including Alternaria. This is particularly valuable because fungal genomes can vary greatly in quality and annotation. Ultimately, Buscogeny helps transform massive amounts of genomic data into an understandable evolutionary story. Each DNA sequence becomes a clue, each conserved gene becomes a landmark, and together these clues reveal a picture of how life is connected.

More at https://link.springer.com/article/10.1007/s10123-025-00752-6?

In comparative genome analysis work, we usually compare more than two genomes and looks for syntenic regions amongst them. In my research I used Evolution Highway (RH) http://eh-demo.ncsa.uiuc.edu/, which is a collaborative project designed to provide a visual means for simultaneously comparing genomes of multiple amniote species. The tool removes the burden of manually aligning these maps and allows cognitive skills to be used toward something more valuable than preparation and transformation of data. In addition to EH, attractive Circos (http://circos.ca/) is also very popular for this kind of analysis.

The EH is available online, and can be easily access and use, whereas Circos installation is not entirely straightforward. One of the most difficult parts of the installation involves installing the GD library. Since there weren't good instructions for installing this library on the internet I decided to post instructions here in case they are useful to anyone else.

Following are the steps to install GD modules in Mac OS

1. Setup

Create a folder for the files:

$ mkdir -p /SourceCache
$ cd /SourceCache

Get and unpack the required Jpeg-6b and GD libraries:
Download Jpeg-6b (http://code.google.com/p/google-desktop-for-linux-mirror/downloads/detail?name=jpeg-6b.tar.gz&can=2&q)
Download GD (http://search.cpan.org/~lds/GD-2.46/)

Place the "tar.gz" files in "/SourceCache" and double click to unpack.

2. Install libjpeg

Copy the "config.sub" and "config.guess" files to "/SourceCache". Note that your "config.sub" and ""config.guess" files may be in a slightly different location. The commands below show where they were on my machine:

$ cd /SourceCache/jpeg-6b/src
$ cp /usr/share/libtool/config/config.sub .
$ cp /usr/share/libtool/config/config.guess .

Configure libjpeg as follows. Note that this was installed on a 64 bit machine. However, this method may configure it in a 32 bit format. This may not be the best way to configure the installation but it works.

$ .configure --enable-shared
$ make

Check to see if the following directories exist on your machine. Create the missing directories in the following manner:

$ mkdir -p /usr/local/include
$ mkdir -p /usr/local/bin
$ mkdir -p /usr/local/lib
$ mkdir -p /usr/local/man/man1

Finish making and installing libjpeg:

$ make install

3. Install GD

$ cd /SourceCache/GD-2.46/GD/
$ perl Makefile.PL
$ make
$ make test (optional)
$ make html (optional)
$ make install

Other way for Mac OS
The easiest way to get a lot of these is with a program called Fink, which is similar in nature to the CPAN installer, but installs common GNU utilities. Fink is available from <http://sourceforge.net/projects/fink/>.

Follow the instructions for setting up Fink. Once it's installed, you'll want to run the following as root: fink install gd

It will prompt you for a number of dependencies, type 'y' and hit enter to install all of the dependencies. Then watch it work.

To prevent creating conflicts with the software that Apple installs by default, Fink creates its own directory tree at /sw where it installs most of the software that it installs. This means your libraries and headers for libgd will be at /sw/lib and /sw/include instead of /usr/lib and /usr/local/include. Because of these changed locations for the libraries, the Perl GD module will not install directly via CPAN, because it looks for the specific paths instead of getting them from your environment. But there's a way around that :-)

Instead of typing "install GD" at the cpan> prompt, type look GD. This should go through the motions of downloading the latest version of the GD module, then it will open a shell and drop you into the build directory. Apply below patch to the Makefile.PL file (save the patch into a file and use the command patch < patchfile.)

Then, run these commands to finish the installation of the GD module:

perl Makefile.PL
make
make test
make install
And don't forget to run exit to get back to CPAN.

Install on MS Window, using PPM

C:\Documents and Settings\Owner>ppm
PPM interactive shell (2.2.0) - type 'help' for available commands.
PPM> install GD
Install package 'GD?' (y/N): y
Installing package 'GD'...
Downloading http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW. ...
Installing C:\Perl\site\lib\auto\GD\GD.bs
Installing C:\Perl\site\lib\auto\GD\GD.dll
Installing C:\Perl\site\lib\auto\GD\GD.exp
Installing C:\Perl\site\lib\auto\GD\GD.lib
Installing C:\Perl\html\site\lib\GD.html
Installing C:\Perl\site\lib\GD.pm
Installing C:\Perl\site\lib\qd.pl
Installing C:\Perl\site\lib\auto\GD\autosplit.ix
PPM>


If you can't install it from ppm. You can download it:
http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW.


BTW,All Perl 5.6.1 Modules are located at:

http://ppm.ActiveState.com/PPMPackages/5.6plus/MSW.

Install the Perl GD Module on Linux

$ sudo perl -MCPAN -e shell

Since it was the first time I had run this command on this particular machine I had to answer a lot of questions but simply selected the defaults for everything as this usually works for me. Once in the CPAN shell I entered

$ install Bundle::CPAN

and selected all of the defaults again. Once the CPAN bundle had finished installing I tried to install GD::Graph by typing

$ install GD::Graph

but it failed with hundreds of errors – the first of which was

GD.xs:7:16: error: gd.h: No such file or directory

This was fixed with the following apt-get command (in the bash shell)

$ sudo apt-get install libgd2-xpm-dev

back in the CPAN shell I still couldn’t get GD::Graph to build and I guessed this was because of some left over files from the failed build. I don’t know the command to clean things up inside the CPAN shell and am too lazy to read the docs so I simply went into the .cpan/build directory in my home directory and deleted anything that started with GD – eg

$ rm -rf GD-2.35-HC_vkB

$ rm -rf GDGraph-1.44-Evfibe

and so on. Those strings at the end (VkB and so on) look random so they might be different on your machine. Then I went back into the CPAN shell and ran

$ install GD::Graph

There were a few dependencies which the script fetched and installed for me but everything worked smoothly.

Manual and other Perl Module instalation are mentioned in my previous blog @ http://bioinformaticsonline.com/blog/view/710/how-to-install-perl-modules-manually-using-cpan-command-and-other-quick-ways

Address of the bookmark: http://www.citrusperl.com/

Address of the bookmark: http://cbb.sjtu.edu.cn/course/database/beginning.pdf

Originally design to map the location of objects in a 10 km map IrishGrid includes:

• native support of the Irish Grid System (see http://www.osi.ie/)
• optimize for speed (there's as less as possible data to conversion)
• customized color functions

https://code.google.com/p/irishgrid/downloads/detail?name=irishgrid.pl

Address of the bookmark: https://code.google.com/p/irishgrid/

Bioinformatics Textbook Track

Find more about Rosalind puzzle at http://rosalind.info/problems/list-view/?location=bioinformatics-textbook-track

I will provide solution of all the Rosalind problem with Perl for community.

Check out the right sidebar for more links ...

More at http://cpansearch.perl.org/src/TJPARNELL/

Address of the bookmark: http://cpansearch.perl.org/src/TJPARNELL/

CORE MODULES

Three modules make up the core engine for MCE.

MCE::Core

Provides the Core API for Many-Core Engine. The various MCE options are described here.

MCE::Signal

Temporary directory creation, cleanup, and signal handling.

MCE::Util

Utility functions for Many-Core Engine.

MCE EXTRAS

There are 4 add-on modules for use with MCE.

MCE::Candy

Provides a collection of sugar methods and output iterators for preserving output order.

MCE::Mutex

Provides a simple semaphore implementation supporting threads and processes.

MCE::Queue

Provides a hybrid queuing implementation for MCE supporting normal queues and priority queues from a single module. MCE::Queue exchanges data via the core engine to enable queuing to work for both children (spawned from fork) and threads.

MCE::Relay

Enables workers to receive and pass on information orderly with zero involvement by the manager process while running.

MCE MODELS

The models take Many-Core Engine to a new level for ease of use. Two options (chunk_size and max_workers) are configured automatically as well as spawning and shutdown.

MCE::Loop

Provides a parallel loop utilizing MCE for building creative loops.

MCE::Flow

A parallel flow model for building creative applications. This makes use of user_tasks in MCE. The author has full control when utilizing this model. MCE::Flow is similar to MCE::Loop, but allows for multiple code blocks to run in parallel with a slight change to syntax.

MCE::Grep

Provides a parallel grep implementation similar to the native grep function.

MCE::Map

Provides a parallel map model similar to the native map function.

MCE::Step

Provides a parallel step implementation utilizing MCE::Queue between user tasks. MCE::Step is a spin off from MCE::Flow with a touch of MCE::Stream. This model, introduced in 1.506, allows one to pass data from one sub-task into the next transparently.

MCE::Stream

Provides an efficient parallel implementation for chaining multiple maps and greps together through user_tasks and MCE::Queue. Like with MCE::Flow, MCE::Stream can run multiple code blocks in parallel with a slight change to syntax from MCE::Map and MCE::Grep.

MISCELLANEOUS

Miscellaneous additions included with the distribution.

MCE::Examples

Describes various demonstrations for MCE including a Monte Carlo simulation.

MCE::Subs

Exports functions mapped directly to MCE methods; e.g. mce_wid. The module allows 3 options; :manager, :worker, and :getter.

REQUIREMENTS

Perl 5.8.0 or later. PDL::IO::Storable is required in scripts running PDL.

SOURCE AND FURTHER READING

The source, cookbook, and examples are hosted at GitHub.

• https://github.com/marioroy/mce-perl

• https://github.com/marioroy/mce-cookbook

• https://github.com/marioroy/mce-examples

SEE ALSO

MCE::Shared provides data sharing capabilities for MCE. It includes MCE::Hobo for running code asynchronously.

• MCE::Shared

• MCE::Hobo

Address of the bookmark: https://github.com/marioroy/mce-examples