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== Daniele Merico - HowTo Directory ==

=== Affymetrix Microarray Analysis ===
__Importing raw data and generating standard gene expression metrics__ (signals, calls, etc...)

 * [[DanieleMerico/HowtoDirectory/AffyCelCalSig| Importing Affymetrix CEL files, calculating MAS5 calls and signals]]<<BR>>
 CEL files are the almost-raw files generated after chip image processing by Affymetrix software; <<BR>>
 the "fun" usually starts from the CEL files onwards; here's is the simplest things you can do with CEL files.
 * [[DanieleMerico/HowtoDirectory/ExprSet| Importing Affymetrix CEL files, bothering about the R exprSet object, calculating MAS5 calls and signals]]<<BR>>
 if the experimental design is quite complex, or you are using a function requiring an expression set (exprSet),<<BR>>
 then, sorry, but you probably need to read this part instead of the previous one.

__Data exploration by dimensionality reduction techniques__
 * How to perform  on a data matrix (e.g. expression matrix)
   * [[DanieleMerico/HowtoDirectory/PCA_stats_princomp| using the stats-package function princomp (covariance matrix)]]
   * [[DanieleMerico/HowtoDirectory/PCA_ade4_dudipca| using the ade4-package function dudi.pca (covariance matrix)]]

__Computing Differential Expression__
 * '''2-class methods''' <<BR>>
 these methods require a dicotomic classification of the samples (e.g. case vs control), 
 and reproducibility of samples belonging to the same class
   * [[DanieleMerico/HowtoDirectory/PLGEM| PLGEM]]<<BR>>
   Features:
     * statistic used: corrected signal-to-noise, every gene treated as an independent entity; signal-to-noise is corrected according to an error model for the global estimation of varibility;
       * error model requires: linear relation between signal mean and standard deviation
     * significance: estimated by randomly permuting the data (by column), and computing the statistic;
     * recommended when: the number of replicates is uneven between case and control, with one of the two having very few, or just one replicate; 
     * proteomics: successfully applied to tandem mass-spec proteomics data, where the signal was generated as abundancy-normalized peptide counts (NSAF)<<BR>>
   References
     * Pubmed.ID: 15606915 (main)
     * Pubmed.ID: 18029349 (proteomic application)
   * SAM<<BR>>
   Features:
     * statistic used: corrected signal-to-noise, every gene treated as an independent entity;
     * significance: estimated by randomly permuting the data (by column), and computing the statistic;
     * recommended when: the number of replicates is 3 or more, and even between case and control; 
     * proteomics: unknown<<BR>>
   References:
     * Pubmed.ID: 11309499 (main)

=== General Computational Techniques ===
__Computational Techniques for multi-dimensional data__:

 * [[DanieleMerico/HowtoDirectory/Distances| A few tips on distances]] (especially for binary strings)

=== Tuning Visualization in R ===
__My stuff__:
 * [[DanieleMerico/HowtoDirectory/Boxplots| Hacks for boxplots tuning]]
 * [[DanieleMerico/HowtoDirectory/Identify| interacting with a scatter plot: the < identify > function]]
 * [[DanieleMerico/HowtoDirectory/Legend| drawing a legend in a plot, the < legend > function]]

__For a more general reference__:
 * [[http://research.stowers-institute.org/efg/R/Graphics/Basics/mar-oma/index.htm|A graphical description of the main graphical parameters for R graphs]]<<BR>>
 and [[http://research.stowers-institute.org/efg/R/|a broader how-to for R graphics]]

=== System: R & the Mac ===
 * Where is R installed in the Mac?<<BR>>
 As a former Windows user, I spent an hour trying to answer the following question: what is the f. location of R executables on the Mac? (i.e. where the hell are R files installed?) (where, of course, "f." stands for funny). The answer is quite straightforward if, instead of wasting time looking for them all round your Mac, you just read the R Mac OS X FAQ, under the chapter "uninstalling R". In my system (Mac OS X 10.5.1), the funny location of R files is:
   * Rgui:
   * other R files: __/library/frameworks/R.framework__
     * for arcane reasons, the R plugin for Eclipse requires as folder of R executables: __/Library/Frameworks/R.framework/Versions/.../Resources__ (where "..." is the version currently under use)

=== The Eclipse Plug-in for Mac ===
 * Eclipse can be used as a programming environment for R, and it can be also connected to Subversion (thus catching two pigeons with one bite)
   * [[DanieleMerico/HowtoDirectory/EclipseRplugin| how to install the R plugin for Eclipse]]
   * [[DanieleMerico/HowtoDirectory/EclipseSubversion| how to install the Subversion plugin for Eclipse]]