Important note for Windows users: If you are running Wasabi under R or R studio on Windows, there is a known issue (bug, I would say) that prevents normal operation. Salmon and Sailfish output important extra information like bootstrap samples and the fragment length distribution to a subdirectory of the quantification directory named
aux. Windows, unfortunately, forbids
aux as a folder name. If you are lucky enough to be reading this before running Sailfish/Salmon, you can pass an alternative folder name to the
--auxDir command line option to avoid this issue. Otherwise, we suggest the following work-around. First, rename the
aux subdirectory of each Sailfish/Salmon quantification directory to be a folder name that is not forbidden under Windows e.g.
aux2. Then, open the
cmd_info.json file in the quantification directory, and add the following line:
"auxDir" : "aux2",
Now, things should work normally under windows. Salmon versions (>=0.7.0) use
aux_info as the default folder to avoid this issue. Future releases of Sailfish (>0.10.1) will use a different default name for the auxiliary directory to avoid this issue as well.
What is wasabi?
How to use wasabi
First, you need to install the wasabi package. There are two main ways to accomplish this:
Installation with devtools
devtools, it's easy to install
source("http://bioconductor.org/biocLite.R") biocLite("devtools") # only if devtools not yet installed biocLite("COMBINE-lab/wasabi")
Installation with bioconda
conda create -n wasabi r-wasabi
Loading and using wasabi
Once wasabi is installed, you can load the library with:
Now that wasabi is installed, we can use it to convert the Sailfish / Salmon output into sleuth-compatible format. Imagine we have some samples (Sailfish quant directories) sitting in a data directory:
data/samp1 data/samp2 data/samp3 data/samp4
First, we create a simple vector containing these directories (the
> below is an R prompt):
> sfdirs <- file.path("data", c("samp1", "samp2", "samp3"))
Now, we simply run the
The function will write some status messages to the console and, when it's done, each directory will now contain
abundance.h5 file in a sleuth-compatible format. From this point forward, you can simply run sleuth normally.