Thomas Lesley Sitter – Bioinformatician / Microbiologist / All-round Geek

Hello world, this is me!

Ellow peeps, I’m Lesley.
I ‘m a former BASc Biochemistry and MSc bio-informatics student from the Netherlands. Recently finished PhD in both dry-lab and wet-lab at the Bio-Protection Research Centre and AgResearch in New Zealand .

I worked on finding a correlation between horizontal gene transfer and virulence/survival of several Serratia isolates using next-generation sequencing data and bioinformatics analysis. Currently looking for a new opportunity.

My interests in regards to bio-informatics lie in NGS data, genome assembly, genotyping, comparative genomics, GWAS. But i’m also still very much a microbiologist/molecular biologists that likes to get his hands dirty, with a great interest in microscopy and TEM related techniques.

Bioinformatics blog entries

Roary analysis

For my work i work with genomic data and one tool i enjoy using is Roary. Roary is a orthologous gene clustering tool that uses BLAST to find similar genes, and if their similarity is above a threshold it would consider them being orthologous. Here is an example script how to analyze the output data in R

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Plotting Geo data

This one was a fun one. During my project i had a list of samples we used, and each sample had some minor geographical data attached from where we got it. I some simple summary information and plotted it on a map using R.

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Multi Y-axis plots

This one was a confusing one. Technically putting three different types of data in a comparable plot makes hardly any sense. But my colleague wanted to show that cell growth both in OD and plate counts correlated to protein secretion. I wrote a script to get this done in R without any hassle.

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Plasmid copy from coverage

You can use your NGS data to guestimate the copy number of plasmids by mapping reads to a reference geneome and calculating the coverage distribution of Chromosome vs plasmids. I'll give you an example

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Determining sample qualitfy from read data

There is a lot of information you can extract from your reads and coverage data that can help you decide if you might stumble onto problems later on your workflow, or if you dataset is even worth using to begin with

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Hello world, this is me!

Bioinformatics blog entries

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