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commit 5528014bd185c39936e41ff57b7b78e59dcef809 Author: Andreas Tille <[email protected]> Date: Fri May 20 00:10:11 2016 +0200 Imported Upstream version 1.12.0 --- DESCRIPTION | 6 +++--- NEWS | 11 ++++++++++- R/EBTest.R | 7 +++++++ README.md | 10 +++++++++- build/vignette.rds | Bin 203 -> 201 bytes inst/doc/EBSeq_Vignette.pdf | Bin 946690 -> 969637 bytes man/MedianNorm.Rd | 27 +++++++++++++++++++++++++-- 7 files changed, 54 insertions(+), 7 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index a80992f..d4823ba 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -2,8 +2,8 @@ Package: EBSeq Type: Package Title: An R package for gene and isoform differential expression analysis of RNA-seq data -Version: 1.10.0 -Date: 2015-7-28 +Version: 1.12.0 +Date: 2015-12-8 Author: Ning Leng, Christina Kendziorski Maintainer: Ning Leng <[email protected]> Depends: blockmodeling, gplots, testthat, R (>= 3.0.0) @@ -22,4 +22,4 @@ BuildVignettes: yes biocViews: StatisticalMethod, DifferentialExpression, MultipleComparison, RNASeq, Sequencing NeedsCompilation: no -Packaged: 2015-10-14 02:58:51 UTC; biocbuild +Packaged: 2016-05-04 04:59:18 UTC; biocbuild diff --git a/NEWS b/NEWS index 20cf398..1afc917 100644 --- a/NEWS +++ b/NEWS @@ -1,10 +1,19 @@ +CHANGES IN VERSION 1.11.1 +------------------------ + + + o Fixed a bug in EBTest() which may cause error when performing isoform DE testing 1 sample vs. multiple samples. + CHANGES IN VERSION 1.9.3 ------------------------ o Correct typos in GetDEResults help file. - o Include an additional method for normalization. + o Include an alternative method for normalization. The alternative method is similar to median-by-ratio normalization, + but can deal with the cases when all of the genes/isoforms have at least one zero counts (in which case the + median-by-ratio normalization will fail). This alternative method is developed for single-cell RNA-seq analysis + where the dataset always contains a large amount of zeros. CHANGES IN VERSION 1.9.2 ------------------------ diff --git a/R/EBTest.R b/R/EBTest.R index ddd9e74..234f194 100644 --- a/R/EBTest.R +++ b/R/EBTest.R @@ -342,7 +342,14 @@ RealName.PoolVarList=sapply(1:NoneZeroLength,function(i)PoolVar[names(PoolVar)%i RealName.QList1=sapply(1:NoneZeroLength,function(i)GetPSP[[1]][names(GetPSP[[1]])%in%NameList[[i]]], simplify=F) RealName.QList2=sapply(1:NoneZeroLength,function(i)GetPSP[[2]][names(GetPSP[[2]])%in%NameList[[i]]], simplify=F) +if(is.null(unlist(RealName.QList1)))RealName.QList1=RealName.QList2 +if(is.null(unlist(RealName.QList2)))RealName.QList2=RealName.QList1 +if(is.null(unlist(RealName.C1VarList)))RealName.C1VarList=RealName.C2VarList +if(is.null(unlist(RealName.C2VarList)))RealName.C2VarList=RealName.C1VarList + + +#browser() for (i in 1:NoneZeroLength){ tmp=NameList[[i]] names=IsoNamesIn[tmp] diff --git a/README.md b/README.md index f876425..f5ad7cc 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ # EBSeq Q & A -## ReadIn data +## Read in data csv file: @@ -124,3 +124,11 @@ Then we will get 4 false positive calls. Cross-sample TPM/FPKM/RPKM comparisons will be feasible only when no hypothetical DE genes present across samples (Or when assuming the DE genes are sort of 'symmetric' regarding up and down regulation). +## RealFC vs PostFC + +The posterior fold change estimations will give less extreme values +for low expressers. e.g. if gene1 has mean1 = 5000 and mean2 = 1000, +its FC and PostFC will both be 5. If gene2 has mean1 = 5 and mean2 = +1, its FC will be 5 but its PostFC will be < 5 and closer to 1. +Therefore when we sort the PostFC, gene2 will be less significant than +gene1. diff --git a/build/vignette.rds b/build/vignette.rds index 489e54e..14c49ac 100644 Binary files a/build/vignette.rds and b/build/vignette.rds differ diff --git a/inst/doc/EBSeq_Vignette.pdf b/inst/doc/EBSeq_Vignette.pdf index 2ba03da..098f62f 100644 Binary files a/inst/doc/EBSeq_Vignette.pdf and b/inst/doc/EBSeq_Vignette.pdf differ diff --git a/man/MedianNorm.Rd b/man/MedianNorm.Rd index afc1475..a86323a 100644 --- a/man/MedianNorm.Rd +++ b/man/MedianNorm.Rd @@ -4,14 +4,37 @@ Median Normalization } \description{ -'MedianNorm' specifies the median normalization function from Anders et. al., 2010. +'MedianNorm' specifies the median-by-ratio normalization function from Anders et. al., 2010. } \usage{ MedianNorm(Data, alternative = FALSE) } \arguments{ \item{Data}{The data matrix with transcripts in rows and lanes in columns.} - \item{alternative}{if alternative = TRUE, the alternative version of median normalization will be applied.} + \item{alternative}{if alternative = TRUE, the alternative version of median normalization will be applied. + The alternative method is similar to median-by-ratio normalization, but can deal with the cases when all of the + genes/isoforms have at least one zero counts (in which case the median-by-ratio normalization will fail). + + In more details, in median-by-ratio normalization (denote l_1 as libsize for sample +1 as an example, assume total S samples): + +hat{l_1} = median_g [ X_g1 / (X_g1*X_g2*...*X_gS)^{-S} ] (1) + +which estimates l_1 / (l_1 * l_2 * ... * l_S)^{-S}. +Since we have the constrain that (l_1 * l_2 * ... * l_S) = 1, equation +(1) estimates l_1. Note (1) could also be written as: + +hat{l_1} = median_g [ (X_g1/X_g1 * X_g1/X_g2 * .... * X_g1/X_gS)^{-S}] + +In the alternative method, we estimate l_1/l_1, l_1/l_2, ... l_1/l_S +individually by taking median_g(X_g1/X_g1), median_g(X_g1/X_g2) ... +Then estimate l_1 = l_1 / (l_1 * l_2 * ... * l_S)^{-S} by taking the +geomean of these estimates: + +hat{l_1} = [ median_g(X_g1/X_g1) * median_g(X_g1/X_g2) * +median_g(X_g1/X_g3) * ... * median_g(X_g1/X_gS) ] ^{-S} + + } } \value{The function will return a vector contains the normalization factor for each lane.} -- Alioth's /usr/local/bin/git-commit-notice on /srv/git.debian.org/git/debian-med/r-bioc-ebseq.git _______________________________________________ debian-med-commit mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/debian-med-commit
