Blog Archives

Utilizing multiple cores in R

February 8, 2011
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There are a couple of options in R, if you want to utilize multiple cores on your machine. These days my favorite is doMC package, which depends on foreach and multicore packages.in the section below squareroot for each number is calculated in parallel...

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command line options in R: "optparse" package

February 8, 2011
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C/python style option parsing now available in R with "optparse" package. Check the documentation here and see below to see how it worksuser@node002 scripts $ Rscript filter.transcripts.by.ncRNA.R -husage:  usage: filter.transcripts.by.ncRNA.R [op...

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command line options in R: "optparse" package

February 8, 2011
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C/python style option parsing now available in R with "optparse" package. Check the documentation here and see below to see how it worksuser@node002 scripts $ Rscript filter.transcripts.by.ncRNA.R -husage:  usage: filter.transcripts.by.ncRNA.R [op...

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sqldf and grouping rows in R

February 8, 2011
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In R, you can treat tables (or data.frames as they are called in R) as SQL tables. That means you can query them as you would query a database with SQL commands. This is particularly useful 1) if you know SQL, hahah:)  2) if you have large tabl...

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sqldf and grouping rows in R

February 8, 2011
By

In R, you can treat tables (or data.frames as they are called in R) as SQL tables. That means you can query them as you would query a database with SQL commands. This is particularly useful 1) if you know SQL, hahah:)  2) if you have large tabl...

Read more »

Principal Component Analysis: Which variables contribute most to principal components ?

November 23, 2010
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Principal component analysis (PCA) is a mathematical transformation of possibly(correlated) variables into a number of uncorrelated variables called principal components. The resulting components from this transformation is defined in such a way that t...

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Principal Component Analysis: Which variables contribute most to principal components ?

November 23, 2010
By

Principal component analysis (PCA) is a mathematical transformation of possibly(correlated) variables into a number of uncorrelated variables called principal components. The resulting components from this transformation is defined in such a way that t...

Read more »