In which I share some iPython code for an interactive demo to calculate and visualise the probability that a positive test implies a positive result. You can get it here, and preview it here. Then I get entangled in a topic outwith my expertise.
A science blog, by a scientist, mostly about computational biology and plant science, but a little rambly in places.
Showing posts with label statistics. Show all posts
Showing posts with label statistics. Show all posts
Friday, 11 July 2014
Sunday, 10 November 2013
ANI are you okay? Are you okay ANI?
In which I describe Average Nucleotide Identity (ANI), which we can use to pigeonhole bacteria into conceptual boxes labelled as 'species'. And I share more code.
Labels:
ANI,
bioinformatics,
biology,
biopython,
BLAST,
DNA,
genome,
github,
MUMmer,
phylogenetics,
phylogenomics,
science,
script,
scripting,
scripts,
sequence,
sequence analysis,
sequencing,
statistics,
visualisation
Sunday, 10 March 2013
Wednesday, 13 February 2013
A Nice New Paradox
In which I work through a popular statistical puzzle/paradox (with potential implications for interpretation of large data studies). With example code.
Thursday, 19 July 2012
On Reciprocal Best BLAST Hits
In which I narrowly avoid a rant. Reciprocal best BLAST hits can improve the quality of your searching, and are a good way to find candidate orthologues. There's evidence and everything.
Sunday, 1 July 2012
Dead fish, and multiple-test correction
In which a salmon is resurrected, but not enough to really be significant. Why finding 20 positive results when your P-value threshold suggests you should only see 10 isn't necessarily anything to be excited about. And an introduction to Bonferroni and Benjamini-Hochberg multiple test correction.
Saturday, 23 June 2012
The Base Rate Fallacy in Effector-Finding
In which an oft-overlooked bit of genome-mining statistics is considered, and your enjoyment of a holiday could depend heavily on other people's hygiene.
Sunday, 16 January 2011
New plots for old kinetics
In which basic enzyme kinetics are revisited, systematically incorrect lab statistics are bemoaned, and a little-known elegant 40 year old solution to estimating enzyme kinetic parameters is explored.
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