[med-svn] [r-bioc-edger] 04/04: Adapt patches

[Andreas Tille]

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tille pushed a commit to branch master
in repository r-bioc-edger.

commit 8aaa616f8386060dce0ea9a9b7563ec38fc5b1e5
Author: Andreas Tille <tille at debian.org>
Date:   Tue Nov 3 14:40:01 2015 +0100

    Adapt patches
---
 debian/patches/do_not_attempt_locfit_test.patch | 32 ++++++++++++-------------
 1 file changed, 15 insertions(+), 17 deletions(-)

diff --git a/debian/patches/do_not_attempt_locfit_test.patch b/debian/patches/do_not_attempt_locfit_test.patch
index 6cbc775..98653d5 100644
--- a/debian/patches/do_not_attempt_locfit_test.patch
+++ b/debian/patches/do_not_attempt_locfit_test.patch
@@ -38,23 +38,21 @@ Description: r-cran-locfit has a non-free license and thus can not be packaged
  group <- factor(c(1,1,2,2))
 --- a/tests/edgeR-Tests.Rout.save
 +++ b/tests/edgeR-Tests.Rout.save
-@@ -264,19 +264,6 @@ $AveLogCPM
- 995 more elements ...
- 
+@@ -296,17 +296,6 @@ Loading required package: splines
+    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
+  0.1385  0.1792  0.1964  0.1935  0.2026  0.2709 
  > 
--> d2 <- estimateDisp(d, design)
--> summary(d2$tagwise.dispersion)
--   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
--0.05545 0.09511 0.11620 0.11010 0.13330 0.16860 
--> d2 <- estimateDisp(d, design, prior.df=20)
--> summary(d2$tagwise.dispersion)
--   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
--0.04203 0.08587 0.11280 0.11010 0.12370 0.37410 
--> d2 <- estimateDisp(d, design, robust=TRUE)
--> summary(d2$tagwise.dispersion)
+-> dglm2 <- estimateDisp(dglm, design)
+-> summary(dglm2$tagwise.dispersion)
 -   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
--0.05545 0.09511 0.11620 0.11010 0.13330 0.16860 
+- 0.1766  0.1789  0.1814  0.1846  0.1870  0.2119 
+-> dglm2 <- estimateDisp(dglm, design, prior.df=20)
+-> summary(dglm2$tagwise.dispersion)
+-   Min. 1st Qu.  Median    Mean 3rd Qu.    .6684268  0.7357761 17.33529  1.7309951 0.420842115 0.90967967
+-2  1.2080938 -0.1660740 18.24544  1.0496688 0.591653347 0.90967967
+-4  0.5416704 -0.6923084 17.57744  0.3958596 0.820427427 0.90967967
+-3  0.2876249 -0.4884392 18.06216  0.1893255 0.909679672 0.90967967
 -> 
- > # Exact tests
- > y <- matrix(rnbinom(20,mu=10,size=3/2),5,4)
- > group <- factor(c(1,1,2,2))
+ > # spliceVariants
+ > z = matrix(c(2,0,4,6,4,3,7,1,1,0,1,1,0,3,1,2,0,1,2,1,0,3,1,0), 8, 3)
+ > gz = c(1,2,2,2,2,2,2,2)

-- 
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