Moderator: David W
David W ♦ 4.7k
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Posts by David W
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Comment:
C: Watterson's estimator "theta"
... Maybe read this, then ask a more specific question if you are still unclear? https://en.wikipedia.org/wiki/Watterson_estimator
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written 4.7 years ago by
David W ♦ 4.7k
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... I don't know if it can be used in the particular case you are taking about, but genome query tools (https://github.com/ryanlayer/gqt) has been written specifically to handle very large genotype files and with low memory footprint and speedy queries.
EDIT
Some of gqt's tricks are specifically for ...
written 4.7 years ago by
David W ♦ 4.7k
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... I recently ran a similar task to the OPs with the mask saved as BED files. First time I ran it'd forgotten to tabix the files: ~7hrs to run. Once I'd tabixed them ~ 1 minute :)
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written 4.7 years ago by
David W ♦ 4.7k
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... This seems to be a problem with the Bioproject database not having a DTD:
http://lists.open-bio.org/pipermail/biopython/2015-May/015632.html
That thread has a work-around, but you might also want to try the development version of Biopython (https://github.com/biopython/biopython)to see if the new ...
written 4.7 years ago by
David W ♦ 4.7k
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... bedtools intersect -a a.bed -b b.bed > intersect_ab.bed
The '>’ bit redirects the output into a (newly created/overwritten) file instead of printing to screen. Welcome to unix-like commands, once you 'get' this and piping you'll find you can do a lot from the command line :-)
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written 4.8 years ago by
David W ♦ 4.7k
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... If you use the link EUtil with dbfrom="protein", db="pubmed" you'll get a list of pmids associated with that protein.
You can then use esummary or efetch on those pmids.
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written 4.8 years ago by
David W ♦ 4.7k
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... Short "answer": to avoid overfitting: http://en.m.wikipedia.org/wiki/Overfitting ...
written 4.8 years ago by
David W ♦ 4.7k
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... Biomart (linked to by Sean above) is pretty much your first port of call for all id-mapping problems.
In this case, ensembl also has a REST endpoint for gathering cross refs:
http://rest.ensembl.org/xrefs/id/ENST00000288602?content-type=application/json;
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written 4.8 years ago by
David W ♦ 4.7k
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... For anyone else interested in the different performance of these solutions, I did a crude comparison.
The TLDR would be: the "grow a for loop" approach works for short vectors, but scales terribly. The rbind method, as unintuitive as it might be, is the fastest of the lot
https://gist.github.c ...
written 4.8 years ago by
David W ♦ 4.7k
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... This should get the job done, and for shorter vectors won't take too long. But be aware, starting an empty vector and growing it like this, though sensible in many languages, is usually very slow in r.
I've not tested it, but as.character(rbind(a,b)) should work, and starting a vector of the final ...
written 4.8 years ago by
David W ♦ 4.7k
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