pombase / website

PomBase website v2
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Check protein properties #611

Closed kimrutherford closed 6 years ago

kimrutherford commented 6 years ago

While working on #569 I noticed that the protein properties we show on the gene pages doesn't match the values in the PeptideStats.tsv file from PomBase V1.

There are many calculators on the web but they give quite different answers for some of the properties. So I'm not sure our values are OK.

As an example, for SPAC3G9.09c we have:

Isoelectric point    6.42
Charge at pH 7      -2.42

(Calculated using this Perl module: http://search.cpan.org/dist/BioPerl/Bio/Tools/pICalculator.pm )

This online calculator matches the values we have quite well (but not perfectly): http://protcalc.sourceforge.net/

Estimated pI = 6.46
Estimated charge at pH 7.00 = -2.4

This one gives somewhat different values: http://pepcalc.com/protein-calculator.php

Iso-electric point: pH 6.03
Net charge at pH 7: -3.5

This one: http://isoelectric.ovh.org/ gives the iso-electric point as: 5.83

Antonialock commented 6 years ago

Maybe it would be good to ask Steve (or someone else at biochemistry) which resource gives the best estimates? Some methods outperform other methods, but I don't know which one is regarded best/reliable.

ValWood commented 6 years ago

Ask pombelist which one people would prefer ?

ValWood commented 6 years ago

@Antonialock maybe you needed to provide the options?

ValWood commented 6 years ago

Also asked Steve's group

Antonialock commented 6 years ago

I wouldn’t know whether to suggest tools or pick algorithms recommended in papers.

Q: do general users even look at the number? Q2: would anyone who cares about the number go out themselves and find an estimate based on their favourite algorithm?

ValWood commented 6 years ago

Let's just pick one, (top google hit?)

ValWood commented 6 years ago

what are the options, we'll decide on the call

Antonialock commented 6 years ago

This paper compares different prediction methods: https://academic.oup.com/bioinformatics/article/32/6/821/1744386

They recommend an SVM based machine learning algorithm published here: https://www.ncbi.nlm.nih.gov/pubmed/22326964

Antonialock commented 6 years ago

Pride

Antonialock commented 6 years ago

https://www.ebi.ac.uk/pride/help/archive

Antonialock commented 6 years ago

https://web.expasy.org/compute_pi/

ValWood commented 6 years ago

document method used currently.

mah11 commented 6 years ago

Documentation done. We decided that will do until & unless users clamor for something different.