v0.18.3

docs/Installation.md

@@ -9,7 +9,7 @@ if you prefer but we recommend [mamba](https://mamba.readthedocs.io/) for faster
 installation and better error messages.
 
 ```
-mamba create -c bioconda -c conda-forge --name singlem singlem'>='0.18.2
+mamba create -c bioconda -c conda-forge --name singlem singlem'>='0.18.3
 ```
 
 Test if it works by running
@@ -23,45 +23,45 @@ After this, you'll also need to procure the reference data (the "metapackage").
 ## Installation via DockerHub
 A docker image generated from the conda package is [available](https://hub.docker.com/r/wwood/singlem) on DockerHub. After installing Docker, run the following:
 ```
-docker pull wwood/singlem:0.18.2
+docker pull wwood/singlem:0.18.3
 ```
 
 Test if it works by running
 ```
-docker run wwood/singlem:0.18.2 -h
+docker run wwood/singlem:0.18.3 -h
 ```
 
 If the sequence data to be analyzed is in the current working directory, SingleM `pipe` can be used like so:
 ```
-docker run -v `pwd`:`pwd` wwood/singlem:0.18.2 pipe --sequences \
+docker run -v `pwd`:`pwd` wwood/singlem:0.18.3 pipe --sequences \
     `pwd`/my.fastq.gz -p `pwd`/my.profile.csv --threads 4
 ```
 Two things to note:
 
 1. The default SingleM reference data is included in the docker image, so running [singlem data](/tools/data) is not necessary for this installation method - you can jump straight to using `pipe`.
-2. You should not specify `singlem` in the command line, as this is automatic. Simply use e.g. `docker run wwood/singlem:0.18.2 pipe -h`.
+2. You should not specify `singlem` in the command line, as this is automatic. Simply use e.g. `docker run wwood/singlem:0.18.3 pipe -h`.
 
 
 ## Installation via Singularity / Apptainer
 SingleM can be installed via [Singularity](https://sylabs.io/singularity/) or [Apptainer](https://apptainer.org). After installing Singularity or Apptainer, run the following:
 ```
-singularity pull docker://wwood/singlem:0.18.2
+singularity pull docker://wwood/singlem:0.18.3
 ```
 
 Test if it works by running
 ```
-singularity run singlem_0.18.2.sif -h
+singularity run singlem_0.18.3.sif -h
 ```
 
 If the sequence data to be analyzed is in the current working directory, SingleM `pipe` can be used like so:
 ```
-singularity run -B `pwd`:`pwd` singlem_0.18.2.sif pipe --sequences \
+singularity run -B `pwd`:`pwd` singlem_0.18.3.sif pipe --sequences \
     `pwd`/my.fastq.gz -p `pwd`/my.profile.csv --threads 4
 ```
 Two things to note:
 
 1. The default SingleM reference data is included in the docker image, so running [singlem data](/tools/data) is not necessary for this installation method - you can jump straight to using `pipe`.
-2. You should not specify `singlem` in the command line, as this is automatic. Simply use e.g. `singularity run singlem_0.18.2.sif pipe -h`.
+2. You should not specify `singlem` in the command line, as this is automatic. Simply use e.g. `singularity run singlem_0.18.3.sif pipe -h`.
 
 
 ## Installation via PyPI

singlem/version.py

@@ -1 +1 @@
-__version__ = "0.18.2"
+__version__ = "0.18.3"