Monthly Archives: October 2013

Data Preparation – Part I

October 31, 2013
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Data Preparation – Part I

The R language provides tools for modeling and visualization, but is still an excellent tool for handling/preparing data. As C++ or python, there is some tricks that bring performance, make the code clean or both, but especially with R these choices can have a huge impact on performance and the “size” of your code. A The post Data...

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Real-time streaming differential RNA-seq analysis with eXpress

October 31, 2013
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Real-time streaming differential RNA-seq analysis with eXpress

RNA-seq has been performed routinely for at least 5+ years, yet there is no consensus on the best methodology for analyzing this data. For example, Eduardo Eyras's group recently posted a pre-print on methods to study splicing from RNA-seq, where this ...

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Simulation of an Oxford (Undergrad) Interview Question

October 31, 2013
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Simulation of an Oxford (Undergrad) Interview Question

A friend of mine, who's an economics teacher in London, is responsible for preparing some of his students for interviews at Oxford and Cambridge. He told me that, at these schools, students have to go through a nerve-wracking...

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Finding R in a Hadoop World

October 31, 2013
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Finding R in a Hadoop World

by Joseph Rickert The following is a brief report of all things R encountered in my not quite random, but nevertheless far from determined, walk through the O'Reilly Strata / Hadoop World Conference held this week in NYC. To start off, I had the pleasure of doing a 9:00 AM Monday morning joint tutorial with Antonio Piccolboni, the principal...

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4th MilanoR meeting: please leave a comment

October 31, 2013
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4th MilanoR meeting took place on October, 24. More than thirty R users and a lot of enthusiasm! You can download presentations and view pictures of the meeting. If you attended the meeting, please leave a comment. Stay connected! Next … Continue reading →

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Photos of the 4th MilanoR meeting

October 31, 2013
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Photos of the 4th MilanoR meeting

Photos of the 4th MilanoR meeting Milano; October 24, 2013

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Reshape and aggregate data with the R package reshape2

October 31, 2013
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Reshape and aggregate data with the R package reshape2

Creating molten data Instead of thinking about data in terms of a matrix or a data frame where we have observations in the rows and variables in the columns, we need to think of the variables as divided in two groups: identifier and measured variables. Identifier variables (id) identify the unit that measurements take place

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Visual interpretation of interaction terms in linear models with ggplot #rstats

October 31, 2013
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Visual interpretation of interaction terms in linear models with ggplot #rstats

I haven’t used interaction terms in (generalized) linear model quite often yet. However, recently I have had some situations where I tried to compute regression models with interaction terms and was wondering how to interprete the results. Just looking at the estimates won’t help much in such cases. One approach used by some people is

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Presentations of the 4th MilanoR meeting

October 31, 2013
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Welcome presentation Nicola Sturaro, Meeting organizer (download PDF, 0.6 MB) R and Microsoft Office Nicola Sturaro, Consultant at Quantide (download PDF, 0.5 MB) Functions returning functions: closures Andrea Spanò, Partner at Quantide (download PDF, 0.5 MB) First steps in parallel … Continue reading →

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Halloween and candies (a ballot problem)

October 30, 2013
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Halloween and candies (a ballot problem)

This year, for Halloween, a post on candies (I promise, next year I will write another post on zombies). But I don’t want to focus on the kids problems (last year, we tried to minimize their walking distance to collect as much candies as possible, with part 1 and part 2), I want to discuss my own problems. Because usually, the kids wear...

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