This file provides a brief description about the changes. Changes summary: Version 1.6.0 ------------- - Changed the name of the function "mt.rawp2adjp" to "mt.rawp2adjp.LPE" in order to avoid conflict with the original function from multtest library. - Added the references to paired LPE - "LPEP library" and LPE for multiple conditions - "HEM library". - Added an option "Bonferroni" in fdr.adjust.R to get Bonferroni adjusted p-values. (Though it is recommended to use FDR, Bonferroni adjusted method has been added here for users who want it.) - Updated the document 'LPE.pdf' (hands on demonstration of LPE) in inst/doc. Changes summary: Version 1.3.0 ------------- Updated the file am.trans.R for faster computations. Version 1.2.0 ______________ - Created a project called "r-lpe" on sourceforge to get the most recent files. One can keep track of changes and checkout the latest version by anonymously checking out lpe from sf.net: cvs -z3 -d:pserver:anonymous@cvs.sourceforge.net:/cvsroot/r-lpe co -P LPE - Bug fix in baseOlig.error.step1 and baseOlig.error.step2: For some data sets, adjacent quantile values were same due to thresholding/nature of the data - which caused the number of genes to be selected for var(M) caluclation as 0, and hence there was an error: "Error in var(x) : 'x' is empty". - Added a check in baseOlig.error.step1 and baseOlig.error.step2 to see if min. value of variance does NOT go negative. - Updated the email address. New address is: - Changed the default value of the parameter probe.set.name to NULL, so that if the GeneIDs are not provided, then rownames (1,2,3,...) are considered as GeneIDs. - Changed the default argument of preprocess function 'lowess=TRUE' to FALSE. User should specify if they need lowess transformation. - Added a reference (new published paper on "rank-invariant resampling for FDR calculations. Version 1.1.5 ______________ - More robust detection of outliers in two sample comparison. (Thanks to HyungJun Cho for the correction). - Function lpe.R is broken in several small functions, easier to understand. - Built under R 2.0.0