Lennart's weblog

Notes about open source software, computers, other stuff.

Month: September 2013

Showing other users (from LDAP) in the LightDM greeter

23 September 2013 / / 0 Comments

Ubuntu Linux uses the LightDM greeter (the login screen you see after booting). Since I’m using an LDAP server to store my user accounts and LightDM by default only shows local users I needed to tell LightDM to give me an ‘other user’ option where I can enter a user name and password (I first checked to see if my LDAP connection work by logging in with an LDAP user from the console (tty1).
LightDM is configured in /etc/lightdm/lightdm.conf, but also provides command line tools to set the options. To show the ‘other user’ use:

sudo /usr/lib/lightdm/lightdm-set-defaults --show-manual-login true

This will disable the user list. It adds the line

greeter-show-manual-login=true

to the lightdm.conf file.
If you only want to see the “Other” entry run:

sudo /usr/lib/lightdm/lightdm-set-defaults --hide-users true

And lastly you can turn off guest:

sudo /usr/lib/lightdm/lightdm-set-defaults --allow-guest false

Thanks to mfish at askubuntu.com!

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Doing a quick fixed-effects meta-analysis using the Rmeta package

3 September 2013 / / 0 Comments

This is a quick example of how to do a fixed meta-analysis using the R package Rmeta, just so I dont have to look it up again next time:

## Create data frame containing betas and standard errors
df <- data.frame()
df <- rbind(df, c(2., 0.2))
df <- rbind(df, c(2.5, 0.4))
df <- rbind(df, c(2.2, 0.2))
 
## Add study names
df <- cbind(df, c("study 1", "study 2", "study 3"))
 
colnames(df) <- c("beta", "se_beta", "name") 
 
## Do the meta-analysis 
ms <- meta.summaries(df$beta, df$se_beta, names=df$name)
 
## Add some colors
mc <- meta.colors(summary="darkgreen", zero="red")
 
## Make a forest plot
plot(ms, xlab=expression(beta ~ " (mmol/l)"), 
     ylab="Study", colors=mc, zero=2.6)

The resulting plot looks like this:
Forest plot of fake data

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ProbABEL v0.4.1 released

3 September 2013 / / 0 Comments

Last week I released v0.4.1 of ProbABEL, just a few days after releasing v0.4.0, which contained a small, but irritating bug.

This release took quite some time to create, but features quite a few bug fixes, including a major one: for the first time since the filevector format was introduced somewhere in 2009/2010, the Cox proportional hazards regression module works with filevector/DatABEL files. This is a major step forward, because up till now we had to maintain two branches of code: trunk, with all the regular updates and improvements, and the old branch that contained the Cox PH module that was only capable of reading text files.

Another notable change is the incorporation of \chi^2 values in the output files. At the moment these are based on the LRT (likelihood ratio test), except where that doesn’t make sense (e.g. when using the --mmscore option. The implementation was relatively easy, because part of the code was still there from previous versions; it was disabled however, because it didn’t deal with missing genotype data. Now it does. Using the LRT is also easier in the case of the 2df (or genotypic) genetic model, where using the Wald test is not straightforward.

The third user-visible change was a change in the [code]probabel.pl[/code] script that hides some of the details (e.g. the location of the files with genotype data) of running a regression for the user. Previously, using the -o option meant that the output file name was constructed from the name of the phenotype file, the argument of the -o option and a fixed extension that depends on the model(s) being run. Starting with v.0.4.0 this behaviour has changed. If the -o option is specified its argument is used as the start of the output file name, with only the fixed extension appended to it. This allows users to specify output in a different directory than the one where the phenotype file was created.

Packages for Ubuntu Linux (or one of its derivatives and probably also Debian) can be found in the GenABEL PPA (personal package archive). Previously we also released pre-compiled Windows binaries, but I’ve stopped doing that. They were never tested anyway, and I think there isn’t much demand for them anyway. Most people who do genome-wide association studies use Linux servers anyway.

Development of ProbABEL (and other members of the GenABEL suite) takes place on this R-forge page. If you are in search of an open source project to contribute to, feel free to contact us!

User support for the GenABEL suite can be found at our forum.

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