Added more detailed description of -widv option following Xiang's description given in Issue #59.

4 files changed, 9 insertions, 4 deletions

diff --git a/doc/manual.pdf b/doc/manual.pdf
index bc2181a..1e9e7b3 100644
--- a/doc/manual.pdf
+++ b/doc/manual.pdf
diff --git a/doc/manual.tex b/doc/manual.tex
index c0119dc..ce24ba5 100644
--- a/doc/manual.tex
+++ b/doc/manual.tex
@@ -1454,7 +1454,7 @@ source code for detailed examples.
 \item  \textcolor{red}{ -d        [filename]}     \quad  specify input eigen value file name
 \item  \textcolor{red}{ -u        [filename]}     \quad  specify input eigen vector file name
 \item  \textcolor{red}{ -c        [filename] }     \quad      specify input covariates file name (optional); an intercept term is needed in the covariates file
-\item  \textcolor{red}{ -widv        [filename] }     \quad      specify input weight file name; this is only used for weighting the residual variance of different individuals
+\item  \textcolor{red}{ -widv        [filename] }     \quad      weight file contains a column of positive values to be used as weights for residuals---each weight corresponds to an individual, in which a high weight corresponds to high residual error variance for this individual (similar in format to phenotype file)
 \item  \textcolor{red}{ -gxe        [filename] }     \quad      specify input environmental covariate file name; this is only used for detecting gene x environmental interactions
 \item  \textcolor{red}{ -cat        [filename] }     \quad      specify input SNP category file name; this is only used for variance component estimation using summary statistics
 \item  \textcolor{red}{ -beta        [filename] }     \quad      specify input beta/z file name; this is only used for variance component estimation using summary statistics
diff --git a/example/demo.txt b/example/demo.txt
index c8082b9..9452e04 100644
--- a/example/demo.txt
+++ b/example/demo.txt
@@ -113,8 +113,9 @@ chr	rs	ps	n_miss	allele1	allele0	af	beta_1	beta_2	Vbeta_1_1	Vbeta_1_2	Vbeta_2_2
 
 # The pve estimates in the log file are based on the standard linear model (i.e. on the observed scale), and so you will need to properly transform it back to the liability scale
 
-## To generate relatedness matrix based on the training data
-../bin/gemma -g mouse_hs1940.geno.txt.gz -p mouse_hs1940.pheno.txt -n 2 -a mouse_hs1940.anno.txt -gk 1 -o mouse_hs1940_CD8_train
+## To generate relatedness matrix based on the training data.
+../bin/gemma -g mouse_hs1940.geno.txt.gz -p mouse_hs1940.pheno.txt -n 2 \
+  -a mouse_hs1940.anno.txt -gk 1 -o mouse_hs1940_CD8_train
 
 # This matrix will only be required if you want to do prediction based on estimated breeding values
 # Prediction can also be done without using the breeding values but instead using the alphas. This later approach does not appear to lose much accuracy in many examples we have encountered, although this may not be the case in your data.
diff --git a/src/gemma.cpp b/src/gemma.cpp
index 906b426..4c22329 100644
--- a/src/gemma.cpp
+++ b/src/gemma.cpp
@@ -323,7 +323,11 @@ void GEMMA::PrintHelp(size_t option) {
     cout << "                  ..." << endl;
     cout << "          missing value: NA" << endl;
     cout << " -widv   [filename]     "
-         << " specify input file that contains a column of residual weights"
+         << " weight file contains a column of positive values to be used "
+         << "as weights for residuals---each weight corresponds to an "
+         << "individual, in which a high weight corresponds to high "
+         << "residual error variance for this individual (similar in "
+	 << "format to phenotype file)"
          << endl;
     cout << "          format: variable for individual 1" << endl;
     cout << "                  variable for individual 2" << endl;