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The discussion centers around the dynamics of bioinformatics software development and contrasts it with academic settings. Key points include:

Transition from Solo to Team Development: The podcast delves into the shift from working individually in an academic setting, where a developer might handle everything on a personal computer, to contributing to a larger codebase in a team environment. This transition involves learning how to collaborate effectively, manage code reviews, and adapt to different software development practices.

Professional Growth and Open Source Projects: Kevin shares his experiences from James Madison University and the Virginia Public Health Laboratory, highlighting his journey from developing solo scripts to contributing to larger projects. He discusses the importance of open-source contributions and how making his work public improved its quality and accessibility.

Challenges of Team Coordination and Software Design: The conversation touches upon the complexities of coordinating a team of developers, emphasizing the need for a consistent coding style and structure. They discuss the importance of setting clear guidelines and having a shared understanding of the project's architecture from the start.

Technical Debt and Code Maintenance: The podcast addresses the accumulation of technical debt in large projects and the necessity for periodic reviews and cleanups to ensure consistency and efficiency.

Balancing Technical Complexity with Practicality: Andrew speaks about the balance between over-engineering and practicality in software development, especially in public health contexts where reliability and simplicity are crucial.

Advice for Aspiring Developers: The hosts conclude with advice for academics looking to transition into bioinformatics software development. They suggest being open to learning, embracing humility, and engaging with open-source communities to gain experience in collaborative development and code review processes.

Overall, the podcast provides valuable insights into the unique challenges and rewards of bioinformatics software development, especially for those transitioning from academic research to professional software development.

Ep 22 Bridging Bytes and Biology: The Dynamics of Team-Based Bioinformatics Software Development

Bass boosted. From metal slug 3 final mission.

Metal Slug 3 Music- Bioinformatics (Mission Five Part Six)

On this episode we are joined by Sara Zufan to discuss her PhD journey and recent projects. The episode covers various research experiences and challenges in the field, including the rapid detection of AMR using nanopore sequencing, COVID-19 projects, hepatitis A outbreak investigations, and Lassa virus surveillance in Liberia. The guests share insights into their professional journeys, their experiences working across different continents, and the future of microbial bioinformatics research.

139 Lassa virus genomics

Today we are talking about bioinformatics with Dr. Abel Torres Espin. Abel is an Assistant Professor and Director of the health data DRIVEN lab at the School of Public Health Sciences at the University of Waterloo in Canada. He has worked with...

More info: https://u2fp.org/get-educated/curecast/episode-125.html

SCI & AI (Episode 125)

I needed an old scifi sounding sample to use, so I grabbed a recording of my ramblings on the tree of life hypothesis at burning man...

Dr. 42 - Complicated Question

Giving reverb to music without reverb results in something amazing.

Metal Slug 3 - Bioinformatics with reverb

Acute encephalitis describes a rapidly developing inflammation of the brain. It is a life-threatening disease with a mortality rate of up to 15%.  However, the cause of 37 to 62% of encephalitis cases is not identified, even after a thorough diagnostic investigation. Mark Ellul is a Specialist Registrar in Neurology and Clinical Research Fellow funded by the Association of British Neurologists at IGH. He recently published a paper in Clinical Medicine “Acute encephalitis – diagnosis and management” (http://www.clinmed.rcpjournal.org/content/18/2/155.abstract). He came to talk to us about acute encephalitis and his work searching for new diagnostic tools to help doctors in the emergency room.

Acute Encephalitis - Searching for diagnostic markers

In this episode we identify areas of “Peak-bioinformatics”. There are a lot of existing bioinformatics software out there - more often than not the new tool you want to write already exists or a new tool cannot effectively improve. We discuss this in terms of genome assembly, read mapping and phylogenetics. 

Question and comments? microbinfie@gmail.com

SHOW NOTES
Generally, novel software is not needed if:
There are a plethora of existing tools
The problem is more or less solved or its been shown to be unsolvable
The underlying technology or problem is now obsolete and/or superceded by other methods. 

Multiple sequence aligners:
MAFFT https://mafft.cbrc.jp/alignment/software/
MUSCLE  https://www.drive5.com/muscle/ 
Whole genome aligners:
Mauve  http://darlinglab.org/mauve/mauve.html
Mugsy http://mugsy.sourceforge.net/
Sibellia  http://bioinf.spbau.ru/sibelia
Parsnp https://github.com/marbl/parsnp

Assemblers:
SPADES https://github.com/ablab/spades
Skesa  https://github.com/ncbi/SKESA
Velvet https://www.ebi.ac.uk/~zerbino/velvet/
Abyss https://github.com/bcgsc/abyss
Edena  http://www.genomic.ch/edena.php
Ray http://denovoassembler.sourceforge.net/

Long read assemblies
HGAP https://github.com/PacificBiosciences/Bioinformatics-Training/wiki/HGAP-2.0
Flye https://github.com/fenderglass/Flye
Canu https://github.com/marbl/canu
Ra https://www.biorxiv.org/content/10.1101/656306v1
Unicycler  https://github.com/rrwick/Unicycler

Read mapping
BWA http://bio-bwa.sourceforge.net/ 
Bowtie2 http://bio-bwa.sourceforge.net/
Minimap2 https://github.com/lh3/minimap2 (BWA better for short reads: https://lh3.github.io/2018/04/02/minimap2-and-the-future-of-bwa)
BBtools https://jgi.doe.gov/data-and-tools/bbtools/
BLAST/BLAT: https://genome.ucsc.edu/FAQ/FAQblat.html
SMALT https://www.sanger.ac.uk/science/tools/smalt-0
Snippy https://github.com/tseemann/snippy
Phenix:  https://github.com/phe-bioinformatics/PHEnix

Variant callers
GATK: https://software.broadinstitute.org/gatk/
VIPR: https://www.viprbrc.org/brc/home.spg?decorator=vipr  
Varscan2  http://varscan.sourceforge.net/

Workflow managers
Bespoke example https://github.com/VertebrateResequencing/vr-codebase
Snakemake. https://snakemake.readthedocs.io/en/stable/
Nextflow  https://www.nextflow.io/
Galaxy  https://usegalaxy.org/
Bpipe  https://github.com/ssadedin/bpipe

Phylogenetics:
Raxml - Raxml-NG https://cme.h-its.org/exelixis/software.html 
IQTREE http://www.iqtree.org/ 
FastTree http://www.microbesonline.org/fasttree/ 
BEAST 1&2 https://www.beast2.org/ 
RevBayes  https://revbayes.github.io/

Metagenomics
Taxonomic classification: Megan, Kraken, SIGMA, MIDAS, metaphlan2, mOTUs. 
Assemblers: MetaSpades, metaflye, MEGAHIT, MetaVelvet, a lot of single isolate assemblers have been tweaked to run on metagenomes.
https://github.com/lskatz/Kalamari

AMR
https://github.com/arpcard/amr_curation
https://food-safety-bioinformatics-hackathon.github.io/AMR-protocols/
ABRICATE https://github.com/tseemann/abricate 
ARIBA https://www.sanger.ac.uk/science/tools/ariba 
Too many detection tools:
https://docs.google.com/spreadsheets/d/18XGWpDiaE249qQKDAL7gdBCka0Z1drpA_s3FElfMJe0/edit#gid=0

Other mentioned resources
Mentioned Recent review. 
Zhang W, Chen J, Yang Y, Tang Y, Shang J, Shen B (2011) A Practical Comparison of De Novo Genome Assembly Software Tools for Next-Generation Sequencing Technologies. PLoS ONE 6(3): e17915. https://doi.org/10.1371/journal.pone.0017915
The Assemblerthon: https://assemblathon.org/
Blog post describing that BWA better for short reads: https://lh3.github.io/2018/04/02/minimap2-and-the-future-of-bwa
The science web: https://thescienceweb.wordpress.com/2015/03/23/each-bioinformatician-to-have-their-own-personal-short-read-aligner-by-2016/

01 What bioinformatics software not to write part 1

“We have to remember, I think, Fleming discovered Penicillin in 1928, and it wasn’t until the 40s that they [antibiotics] were able to be mass produced and used on a large scale. The first penicillin-resistant bacteria was discovered in 1947.”

Dr Matt Bawn is tackling antibiotic resistance in salmonella, combining big data and computational biology with single cell analysis to understand the rapid evolution going on at the fine scale; how antibiotic resistance arises in individual bacteria, as well as within large populations.

Here, we explore the reasons behind the rise in multidrug antibiotic resistance, the threat that antibiotic resistance poses to humanity in the very short term, and the methods by which scientists are helping to monitor, diagnose, understand, and fight back against this tremendous global health concern.

Will targeted methods such as ‘phage therapy’ breach the antibiotic void? Will they suffer the same consequences, with bacteria fast developing resistance? Perhaps mining genomes will help us to unearth new therapies? Will we learn not to misuse the last line of defence against what is already the world’s second-biggest killer, causing 20% of global deaths annually?

The problem, perhaps, has been complacency.

“People become complacent because they hear about the evolution of antimicrobial resistance, and as soon as people hear the word evolution, they think - oh, we’ve got a lot of time, because they think that evolution takes a lot of time to work. But what we’ve already seen from our research on salmonella… is that evolution in bacteria can be incredibly quick.” 

As Matt tells us in the podcast: “Unless something drastic happens, very soon, we’re going to enter an era where antibiotics no longer work for routine things, which means that people will die from normal infections, or things at the moment that we’re not considering as very serious.

“Sepsis, at the moment, is the largest killer of people in the world [after cardiovascular disease].”

Imagine the scenario in a post-antibiotic world.

Antibiotic resistance: people will die when antibiotics fail

I Like Music. I Like Sandboxes. I Like Level Editors. I Like Psychotic Stuff. I Like, Eh... Videogames. I Like Good Pals. I Like Music.
 You Cant Return The Slab. Now Get Lost!

I'm scientist and DR42 is my persona who likes to make mashups and techno.

Unite 2 Fight Paralysis exists to unite and empower the international spinal cord injury community to cure paralysis through advocacy, education, and support for research. Get Educated and Get Involved.

The Institute of Infection and Global Health is an international centre of excellence dedicated to improving the health and well-being of humans and animals. We bring together doctors, vets and basic scientists to put Liverpool at the forefront of the 'one health' agenda.

Microbial Bioinformatics is a rapidly changing field marrying computer science and microbiology. Join us as we share some tips and tricks we’ve learnt over the years. If you’re student just getting to grips to the field, or someone who just wants to keep tabs on the latest and greatest - this podcast is for you. 

The hosts are Dr. Lee Katz from the Centres for Disease Control and Prevention (US), Dr. Nabil-Fareed Alikhan from the University of Oxford (UK), and Prof. Andrew Page from Theiagen Genomics (UK) and bring together years of experience in microbial bioinformatics.

The opinions expressed here are our own and do not necessarily reflect the views of Centres for Disease Control and Prevention, University of Oxford or Theiagen Genomics.

Intro music : Werq - Kevin MacLeod (incompetech.com)
Licensed under Creative Commons: By Attribution 3.0 License
http://creativecommons.org/licenses/by/3.0/

Outro music : Scheming Weasel (faster version) - Kevin MacLeod (incompetech.com)
Licensed under Creative Commons: By Attribution 3.0 License
http://creativecommons.org/licenses/by/3.0/

Question and comments? microbinfie@gmail.com

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