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authorPeter Carbonetto2017-05-09 12:48:27 -0500
committerPeter Carbonetto2017-05-09 12:48:27 -0500
commitf808355cd7abbadd2fbcc5ff471ba89a12205159 (patch)
treeb5b9bef67de6b04d70a4c8b67b2e464b9aee343f
parent0f6431e9191acfafc33152a610b87d3d0524c1fe (diff)
downloadpangemma-f808355cd7abbadd2fbcc5ff471ba89a12205159.tar.gz
Putatively fixed -Wc++11-narrowing error in io.cpp (see Issue #24).
-rw-r--r--Makefile.osx2
-rw-r--r--example/demo.txt17
-rw-r--r--src/io.cpp4
3 files changed, 12 insertions, 11 deletions
diff --git a/Makefile.osx b/Makefile.osx
index efa2e4c..8fcab7b 100644
--- a/Makefile.osx
+++ b/Makefile.osx
@@ -30,7 +30,7 @@ SRC_DIR = ./src
CPP = g++
CPPFLAGS = -F /System/Library/Frameworks -Wall -O3 \
- -I/usr/local/opt/gsl@1/include
+ -I/usr/local/opt/gsl@1/include -Wc++11-narrowing
LIBS = /usr/local/opt/gsl@1/lib/libgsl.a \
/usr/local/opt/gsl@1/lib/libgslcblas.a -lz
diff --git a/example/demo.txt b/example/demo.txt
index 766d949..3231ddc 100644
--- a/example/demo.txt
+++ b/example/demo.txt
@@ -1,13 +1,10 @@
-## Detailed description of the data set is available in the online GEMMA user manual
-## Each of the following steps may take over one minute to run
-
-
-
-
-
+## Detailed description of the data set is available in the online
+## GEMMA user manual. Each of the following steps may take over one
+## minute to run.
## To calculate a centered relatedness matrix:
-../bin/gemma -g mouse_hs1940.geno.txt.gz -p mouse_hs1940.pheno.txt -a mouse_hs1940.anno.txt -gk -o mouse_hs1940
+../bin/gemma -g mouse_hs1940.geno.txt.gz -p mouse_hs1940.pheno.txt \
+ -a mouse_hs1940.anno.txt -gk -o mouse_hs1940
# The estimated relatedness matrix should look like this:
0.3350590 -0.0227226 0.0103535 ...
@@ -55,7 +52,9 @@ se(pve) in the null model = 0.032774
## To perform association tests with a multivariate linear mixed model, for two phenotypes CD8 (column 1) and MCH (column 6):
## Notice that the number of individuals in this analysis is different from that above, so the allele frequencies are different between the two analyses
-../bin/gemma -g mouse_hs1940.geno.txt.gz -p mouse_hs1940.pheno.txt -n 1 6 -a mouse_hs1940.anno.txt -k ./output/mouse_hs1940.cXX.txt -lmm -o mouse_hs1940_CD8MCH_lmm
+../bin/gemma -g mouse_hs1940.geno.txt.gz -p mouse_hs1940.pheno.txt \
+ -n 1 6 -a mouse_hs1940.anno.txt -k ./output/mouse_hs1940.cXX.txt \
+ -lmm -o mouse_hs1940_CD8MCH_lmm
# The result for top 5 SNPs should look like this:
chr rs ps n_miss allele1 allele0 af beta_1 beta_2 Vbeta_1_1 Vbeta_1_2 Vbeta_2_2 p_wald
diff --git a/src/io.cpp b/src/io.cpp
index 4da1590..ccaec30 100644
--- a/src/io.cpp
+++ b/src/io.cpp
@@ -2160,7 +2160,9 @@ bool ReadFile_bgen(const string &file_bgen, const set<string> &setSnps, const gs
uint16_t unzipped_data[3*bgen_N];
if (setSnps.size()!=0 && setSnps.count(rs)==0) {
- SNPINFO sInfo={"-9", rs, -9, -9, minor, major, -9, -9, (long int) -9};
+ SNPINFO sInfo={"-9", rs, -9, -9, minor, major,
+ static_cast<size_t>(-9), -9, (long int) -9};
+
snpInfo.push_back(sInfo);
indicator_snp.push_back(0);
if(CompressedSNPBlocks)