ammaraziz/voi
A pipeline based on the Nextstrain for viral outbreak investigations
Overview
Latest release: None, Last update: 2026-04-09
Share link: https://snakemake.github.io/snakemake-workflow-catalog?wf=ammaraziz/voi
Quality control: linting: failed formatting: passed
Deployment
Step 1: Install Snakemake and Snakedeploy
Snakemake and Snakedeploy are best installed via the Conda package manager. It is recommended to install conda via Miniforge. Run
conda create -c conda-forge -c bioconda -c nodefaults --name snakemake snakemake snakedeploy
to install both Snakemake and Snakedeploy in an isolated environment. For all following commands ensure that this environment is activated via
conda activate snakemake
For other installation methods, refer to the Snakemake and Snakedeploy documentation.
Step 2: Deploy workflow
With Snakemake and Snakedeploy installed, the workflow can be deployed as follows. First, create an appropriate project working directory on your system and enter it:
mkdir -p path/to/project-workdir
cd path/to/project-workdir
In all following steps, we will assume that you are inside of that directory. Then run
snakedeploy deploy-workflow https://github.com/ammaraziz/voi . --tag None
Snakedeploy will create two folders, workflow and config. The former contains the deployment of the chosen workflow as a Snakemake module, the latter contains configuration files which will be modified in the next step in order to configure the workflow to your needs.
Step 3: Configure workflow
To configure the workflow, adapt config/config.yml to your needs following the instructions below.
Step 4: Run workflow
The deployment method is controlled using the --software-deployment-method (short --sdm) argument.
To run the workflow using apptainer/singularity, use
snakemake --cores all --sdm apptainer
To run the workflow using a combination of conda and apptainer/singularity for software deployment, use
snakemake --cores all --sdm conda apptainer
To run the workflow with automatic deployment of all required software via conda/mamba, use
snakemake --cores all --sdm conda
Snakemake will automatically detect the main Snakefile in the workflow subfolder and execute the workflow module that has been defined by the deployment in step 2.
For further options such as cluster and cloud execution, see the docs.
Step 5: Generate report
After finalizing your data analysis, you can automatically generate an interactive visual HTML report for inspection of results together with parameters and code inside of the browser using
snakemake --report report.zip
Configuration
The following section is imported from the workflow’s config/README.md.
Workflow overview
This workflow is a best-practice workflow for <detailed description>.
The workflow is built using snakemake and consists of the following steps:
Download genome reference from NCBI
Validate downloaded genome (
pythonscript)Simulate short read sequencing data on the fly (
dwgsim)Check quality of input read data (
FastQC)Collect statistics from tool output (
MultiQC)
Running the workflow
Input data
This template workflow creates artificial sequencing data in *.fastq.gz format.
It does not contain actual input data.
The simulated input files are nevertheless created based on a mandatory table linked in the config.yaml file (default: .test/samples.tsv).
The sample sheet has the following layout:
sample |
condition |
replicate |
read1 |
read2 |
|---|---|---|---|---|
sample1 |
wild_type |
1 |
sample1.bwa.read1.fastq.gz |
sample1.bwa.read2.fastq.gz |
sample2 |
wild_type |
2 |
sample2.bwa.read1.fastq.gz |
sample2.bwa.read2.fastq.gz |
Parameters
This table lists all parameters that can be used to run the workflow.
parameter |
type |
details |
default |
|---|---|---|---|
sample_sheet |
|||
path |
str |
path to sample sheet, mandatory |
“config/samples.tsv” |
get_genome |
|||
ncbi_ftp |
str |
link to a genome on NCBI’s FTP server |
link to S. cerevisiae genome |
simulate_reads |
|||
read_length |
num |
length of target reads in bp |
100 |
read_number |
num |
number of total reads to be simulated |
10000 |
Workflow parameters
The following table is automatically parsed from the workflow’s config.schema.y(a)ml file.
Parameter |
Type |
Description |
Required |
Default |
|---|---|---|---|---|
sample_sheet |
string |
path to sample-sheet TSV file |
yes |
|
get_genome |
yes |
|||
. ncbi_ftp |
string |
URL for genome retrieval |
yes |
|
simulate_reads |
yes |
|||
. read_length |
number |
length of target reads in bp |
||
. read_number |
number |
number of total reads to be simulated |
Linting and formatting
Linting results
1Lints for rule collate (line 1, /tmp/tmp1o9hmsmr/workflow/rules/collate.smk):
2 * No log directive defined:
3 Without a log directive, all output will be printed to the terminal. In
4 distributed environments, this means that errors are harder to discover.
5 In local environments, output of concurrent jobs will be mixed and become
6 unreadable.
7 Also see:
8 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
9
10Lints for rule index (line 58, /tmp/tmp1o9hmsmr/workflow/rules/align.smk):
11 * No log directive defined:
12 Without a log directive, all output will be printed to the terminal. In
13 distributed environments, this means that errors are harder to discover.
14 In local environments, output of concurrent jobs will be mixed and become
15 unreadable.
16 Also see:
17 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
18
19Lints for rule translate (line 123, /tmp/tmp1o9hmsmr/workflow/rules/phylo.smk):
20 * No log directive defined:
21 Without a log directive, all output will be printed to the terminal. In
22 distributed environments, this means that errors are harder to discover.
23 In local environments, output of concurrent jobs will be mixed and become
24 unreadable.
25 Also see:
26 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
27 * Specify a conda environment or container for each rule.:
28 This way, the used software for each specific step is documented, and the
29 workflow can be executed on any machine without prerequisites.
30 Also see:
31 https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
32 https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
33
34Lints for rule extract_cluster_sequences (line 1, /tmp/tmp1o9hmsmr/workflow/rules/snpdist.smk):
35 * No log directive defined:
36 Without a log directive, all output will be printed to the terminal. In
37 distributed environments, this means that errors are harder to discover.
38 In local environments, output of concurrent jobs will be mixed and become
39 unreadable.
40 Also see:
41 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
42
43Lints for rule calc_snpdist_cluster (line 47, /tmp/tmp1o9hmsmr/workflow/rules/snpdist.smk):
44 * No log directive defined:
45 Without a log directive, all output will be printed to the terminal. In
46 distributed environments, this means that errors are harder to discover.
47 In local environments, output of concurrent jobs will be mixed and become
48 unreadable.
49 Also see:
50 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
51
52Lints for rule calc_all_snpdist (line 69, /tmp/tmp1o9hmsmr/workflow/rules/snpdist.smk):
53 * No log directive defined:
54 Without a log directive, all output will be printed to the terminal. In
55 distributed environments, this means that errors are harder to discover.
56 In local environments, output of concurrent jobs will be mixed and become
57 unreadable.
58 Also see:
59 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
60
61Lints for rule plot_tree (line 41, /tmp/tmp1o9hmsmr/workflow/rules/export.smk):
62 * No log directive defined:
63 Without a log directive, all output will be printed to the terminal. In
64 distributed environments, this means that errors are harder to discover.
65 In local environments, output of concurrent jobs will be mixed and become
66 unreadable.
67 Also see:
68 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
69
70Lints for rule plot_snpdist_cluster (line 64, /tmp/tmp1o9hmsmr/workflow/rules/export.smk):
71 * No log directive defined:
72 Without a log directive, all output will be printed to the terminal. In
73 distributed environments, this means that errors are harder to discover.
74 In local environments, output of concurrent jobs will be mixed and become
75 unreadable.
76 Also see:
77 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
78
79Lints for rule plot_snpdist_all (line 84, /tmp/tmp1o9hmsmr/workflow/rules/export.smk):
80 * No log directive defined:
81 Without a log directive, all output will be printed to the terminal. In
82 distributed environments, this means that errors are harder to discover.
83 In local environments, output of concurrent jobs will be mixed and become
84 unreadable.
85 Also see:
86 https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
Formatting results
All tests passed!