There are several pre-computed trees available for display, including the main Tree Of Life, described in Ciccarelli, et al., 2006. In addition to the precomputed trees, users can upload and display personal trees and data, using the 'Data upload' page or through a personal user account.

Address of the bookmark: http://itol.embl.de/

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?

Address of the bookmark: http://tree.bio.ed.ac.uk/software/figtree/

 All the nodes in the tree are clickable. This displays various information and options:

• The species name (and the associated common name if there is one)
• The rank (kingdom, family, class, species...)
• Ability to go to the corresponding node/species on NCBI web site (displayed in a new window)
• Possibility to download the corresponding subtree in newick extended format
• Possibilty to get the whole lineage from the current node/tip to the root of the tree.

Address of the bookmark: http://lifemap-ncbi.univ-lyon1.fr/

The First time when you login to the remotehost from a localhost, it will display the host key not found message and you can give “yes” to continue. The host key of the remote host will be added under .ssh2/hostkeys directory of your home directory, as shown below.

localhost$ ssh -l jit remotehost.example.com

jit@remotehost.example.com password:

remotehost.example.com$

The Second time when you login to the remote host from the localhost, it will prompt only for the password as the remote host key is already added to the known hosts list of the ssh client.

localhost$ ssh -l jit remotehost.example.com
jit@remotehost.example.com password:
remotehost.example.com$

For some reason, if the host key of the remote host is changed after you logged in for the first time, you may get a warning message as shown below. This could be because of various reasons such as 1) Sysadmin upgraded/reinstalled the SSH server on the remote host 2) someone is doing malicious activity etc., The best possible action to take before saying “yes” to the message below, is to call your sysadmin and identify why you got the host key changed message and verify whether it is the correct host key or not.

localhost$ ssh -l jit remotehost.example.com

jit @remotehost.example.com's password:
remotehost$

4. Debug SSH Client:

Sometimes it is necessary to view debug messages to troubleshoot any SSH connection issues. For this purpose, pass -v (lowercase v) option to the ssh as shown below.

Example without debug message:

        localhost$ ssh -l jit remotehost.example.com
        warning: Connecting to remotehost.example.com failed: No address associated to the name
        localhost$

Example with debug message:

        locaclhost$ ssh -v -l jit remotehost.example.com
        debug: SshConfig/sshconfig.c:2838/ssh2_parse_config_ext: Metaconfig parsing stopped at line 3.
        debug: SshConfig/sshconfig.c:637/ssh_config_set_param_verbose: Setting variable 'VerboseMode' to 'FALSE'.
        debug: SshConfig/sshconfig.c:3130/ssh_config_read_file_ext: Read 17 params from config file.
        debug: Ssh2/ssh2.c:1707/main: User config file not found, using defaults. (Looked for '/home/jit/.ssh2/ssh2_config')
        debug: Connecting to remotehost.example.com, port 22... (SOCKS not used)
        warning: Connecting to remotehost.example.com failed: No address associated to

5. Escape Character: (Toggle SSH session, SSH session statistics etc.)

Escape character ~ get’s SSH clients attention and the character following the ~ determines the escape command.
Toggle SSH Session: When you’ve logged on to the remotehost using ssh from the localhost, you may want to come back to the localhost to perform some activity and go back to remote host again. In this case, you don’t need to disconnect the ssh session to the remote host. Instead follow the steps below.

i. Login to remotehost from localhost: localhost$ssh -l jit remotehost
ii. Now you are connected to the remotehost: remotehost$
iii. To come back to the localhost temporarily, type the escape character ~ and Control-Z. When you type ~ you will not see that immediately on the screen until you press and press enter. So, on the remotehost in a new line enter the following key strokes for the below to work: ~

    remotehost$ ~^Z
    [1]+  Stopped                 ssh -l jit remotehost
    localhost$

iv. Now you are back to the localhost and the ssh remotehost client session runs as a typical unix background job, which you can check as shown below:

    localhost$ jobs
    [1]+  Stopped                 ssh -l jit remotehost

v. You can go back to the remote host ssh without entering the password again by bringing the background ssh remotehost session job to foreground on the localhost

    localhost$ fg %1
    ssh -l jit remotehost
    remotehost$

Basic Galaxy Tutorial

• RNA-Seq tutorial based on Trapnell et al. (2012) Nature Protocols

In this tutorial we cover the concepts of RNA-Seq differential gene expression (DGE) analysis using a very small synthetic dataset from a well studied organism.

Advanced Galaxy Tutorial

• RNA-Seq (Advanced) Tutorial

In this tutorial we compare the performance of three statistically-based differential expression tools:

* CuffDiff

* EdgeR

* DESeq2

Advanced Command Line Tutorial

• Graphical Output with CummeRbund introduces some basic commands using the cummeRbund package of the R programming language

You will need to install R, RStudio and cummeRbund on your PC (explained in the Tutorial). You will learn how to produce graphical output from RNA-Seq analysis previously done using a Cuffdiff analysis.

Variant Detection

Basic Galaxy Tutorial

• Variant Detection tutorial

In this tutorial we cover the concepts of detecting small variants (SNVs and indels) in human genomic DNA using a small set of reads from chromosome 22.

Advanced Galaxy Tutorial

• Variant Detection (Advanced) Tutorial

In this tutorial we compare the performance of three statistically-based variant detection tools:

* SAMtools: Mpileup

* GATK: Unified Genotyper

* FreeBayes

Each of these tools takes as its input a BAM file of aligned reads and generates a list of likely variants in VCF format

Pipelines are for those who are comfortable with using the UNIX command line; and often allow more control over branching and iteration logic.

• WGS/exome GATK-based variant calling pipeline

This is a basic variant-calling and annotation pipeline developed at the Victorian Life Sciences Computation Initiative (VLSCI), University of Melbourne. It is based around BWA, GATK and ENSEMBL and was originally designed for human (or similar) data. The master branch is configured for WGS data; there is an exome branch configured for variant calling in exome data.

To run the pipeline you will need Rubra: https://github.com/bjpop/rubra. Rubra uses the python Ruffus library: http://www.ruffus.org.uk/.

Protocols

• Familial Variant Calling

In this protocol we discuss and outline the process of calling familial related mutations.

• Somatic Variant Calling

In this protocol we discuss and outline the process of identifying somatic variants or mutations.

Assembly

Basic Galaxy Tutorial

• Genome assembly tutorial

In this tutorial we carry out de novo assembly of a microbial genome. We have also written a De novo Genome Assembly for Illumina Data Protocol for a more generic description of the method.

Protocol

• De novo Genome Assembly for Illumina Data

In this protocol we discuss and outline the process of de novo assembly for small to medium sized genomes. Use our Genome assembly tutorial to learn a specific case of using Galaxy to carry out de novo assembly of a microbial genome.

Small RNAs

Basic Galaxy Tutorial

• Quality control for small RNA

This tutorial covers initial steps of the workflow for analysis of short RNA expression such as a quality control of the raw reads, processing of the raw reads for the subsequent analysis and initial quality assessment of the library.

ChIP Seq

Protocol

• ChIP-Seq

In this protocol we discuss ChIP-Seq: a method to analyze the interaction between proteins and DNA.

Amplicons

Protocol

• Amplicon Alignment

In this protocol we discuss and outline the process of aligning custom amplicons using primers for high precision.

Learn Galaxy

Introduction to Galaxy, for those who are very new to Galaxy.

Using Histories and Workflows, for those with some Galaxy knowledge.

The Galaxy project website has many tutorials and screencasts about using Galaxy and the tools, and developing new tools.

Address of the bookmark: https://genome.edu.au/wiki/Learn

More at https://pubmed.ncbi.nlm.nih.gov/34951622/

Address of the bookmark: https://github.com/EbmeyerSt/GEnView

Jarvis et al. (2014)

Reference https://link.springer.com/article/10.1007/s00412-018-0685-6

Address of the bookmark: http://christophergandrud.github.io/d3Network/

More recently, we've been enthused about using k-mer based similarity measures and computing and searching k-mer-based sketch search databases for all the things.

But I haven't spent too much talking about using k-mers for taxonomy, although that has become an ahem area of interest recently, if you read into our papers a bit.

In this blog post I'm going to fix this by doing a little bit of a literature review and waxing enthusiastic about other people's work. Then in a future blog post I'll talk about how we're building off of this work in fun! and interesting? ways!

Address of the bookmark: http://ivory.idyll.org/blog/2017-something-about-kmers.html