[med-svn] [r-bioc-ebseq] 02/06: Imported Upstream version 1.12.0
Andreas Tille
tille at debian.org
Thu May 19 22:21:06 UTC 2016
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tille pushed a commit to branch master
in repository r-bioc-ebseq.
commit 5528014bd185c39936e41ff57b7b78e59dcef809
Author: Andreas Tille <tille at debian.org>
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 <lengning1 at gmail.com>
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.}
--
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