r1cheu/imputation

imputation pipeline for low-coverage sequencing in hybrid rice

Overview

Latest release: None, Last update: 2026-05-09

Share link: https://snakemake.github.io/snakemake-workflow-catalog?wf=r1cheu/imputation

Quality control: linting: failed formatting: failed

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/r1cheu/imputation . --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.

Configuration

config.yaml

Key

Meaning

sample_sheet

TSV listing samples (see below)

reference.fasta

Reference genome FASTA (e.g. IRGSP-1.0). Indices are built by the workflow.

panel.vcf

Whole-genome phased reference panel VCF, bgzipped. Will be split per chromosome.

chromosomes

List of chromosome names. Must match both reference and panel.

genetic_map.template

Per-chromosome genetic map path template, e.g. resources/maps/{chrom}.gmap. Format expected by GLIMPSE2: pos chr cM.

glimpse2_chunk.window_mb

GLIMPSE2_chunk --window-mb (default 4.0)

glimpse2_chunk.buffer_mb

GLIMPSE2_chunk --buffer-mb (default 0.5)

glimpse2_chunk.extra

Extra flags passed verbatim to GLIMPSE2_chunk

fastp.extra

Extra flags passed verbatim to fastp (e.g. quality cutoffs)

Threads/memory per rule are hard-coded in workflow/rules/*.smk (tuned for ~600 cores / ~5000 samples). Override by editing those resources: blocks.

samples.tsv

Tab-separated, one sample per row.

Column

Required

Meaning

sample

yes

unique sample id (used as RG ID/SM)

platform

yes

sequencing platform string (RG PL), e.g. ILLUMINA

fq1

yes

path to read 1 fastq.gz

fq2

yes

path to read 2 fastq.gz

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

yes

config/samples.tsv

reference

yes

. fasta

string

path to the reference genome FASTA

yes

panel

yes

. full_template

string

per-chrom full-GT panel BCF template, e.g. “reference/panel_{chrom}.bcf”

yes

. sites_template

string

per-chrom sites-only VCF/BCF template (with .csi/.tbi alongside)

yes

chromosomes

array

chromosome names matching the reference and panel

yes

genetic_map

yes

. template

string

per-chromosome genetic map path template, e.g. “maps/{chrom}.gmap”

yes

glimpse2_chunk

yes

. window_mb

number

yes

4.0

. buffer_mb

number

yes

0.5

. extra

string

fastp

. extra

string

Linting and formatting

Linting results
 1Workflow defines that rule bwa_mem2_index is eligible for caching between workflows (use the --cache argument to enable this).
 2Workflow defines that rule samtools_faidx is eligible for caching between workflows (use the --cache argument to enable this).
 3Workflow defines that rule glimpse2_split_reference is eligible for caching between workflows (use the --cache argument to enable this).
 4Lints for rule bwa_mem2_index (line 1, /tmp/tmpy8zaenw4/workflow/rules/reference.smk):
 5    * Specify a conda environment or container for each rule.:
 6      This way, the used software for each specific step is documented, and the
 7      workflow can be executed on any machine without prerequisites.
 8      Also see:
 9      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
10      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
11
12Lints for rule samtools_faidx (line 23, /tmp/tmpy8zaenw4/workflow/rules/reference.smk):
13    * Specify a conda environment or container for each rule.:
14      This way, the used software for each specific step is documented, and the
15      workflow can be executed on any machine without prerequisites.
16      Also see:
17      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
18      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
19
20Lints for rule fastp_trim (line 1, /tmp/tmpy8zaenw4/workflow/rules/trim.smk):
21    * Specify a conda environment or container for each rule.:
22      This way, the used software for each specific step is documented, and the
23      workflow can be executed on any machine without prerequisites.
24      Also see:
25      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
26      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
27
28Lints for rule bwa_mem2_mem (line 1, /tmp/tmpy8zaenw4/workflow/rules/align.smk):
29    * Specify a conda environment or container for each rule.:
30      This way, the used software for each specific step is documented, and the
31      workflow can be executed on any machine without prerequisites.
32      Also see:
33      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
34      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
35
36Lints for rule mark_duplicates (line 27, /tmp/tmpy8zaenw4/workflow/rules/align.smk):
37    * Specify a conda environment or container for each rule.:
38      This way, the used software for each specific step is documented, and the
39      workflow can be executed on any machine without prerequisites.
40      Also see:
41      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
42      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
43
44Lints for rule index_bam (line 47, /tmp/tmpy8zaenw4/workflow/rules/align.smk):
45    * Specify a conda environment or container for each rule.:
46      This way, the used software for each specific step is documented, and the
47      workflow can be executed on any machine without prerequisites.
48      Also see:
49      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
50      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
51
52Lints for rule glimpse2_chunk (line 1, /tmp/tmpy8zaenw4/workflow/rules/imputation.smk):
53    * Specify a conda environment or container for each rule.:
54      This way, the used software for each specific step is documented, and the
55      workflow can be executed on any machine without prerequisites.
56      Also see:
57      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
58      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
59
60Lints for rule glimpse2_split_reference (line 24, /tmp/tmpy8zaenw4/workflow/rules/imputation.smk):
61    * Specify a conda environment or container for each rule.:
62      This way, the used software for each specific step is documented, and the
63      workflow can be executed on any machine without prerequisites.
64      Also see:
65      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
66      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
67
68Lints for rule make_bam_list (line 51, /tmp/tmpy8zaenw4/workflow/rules/imputation.smk):
69    * Specify a conda environment or container for each rule.:
70      This way, the used software for each specific step is documented, and the
71      workflow can be executed on any machine without prerequisites.
72      Also see:
73      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
74      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
75
76Lints for rule glimpse2_phase (line 66, /tmp/tmpy8zaenw4/workflow/rules/imputation.smk):
77    * Specify a conda environment or container for each rule.:
78      This way, the used software for each specific step is documented, and the
79      workflow can be executed on any machine without prerequisites.
80      Also see:
81      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
82      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
83
84Lints for rule glimpse2_ligate (line 86, /tmp/tmpy8zaenw4/workflow/rules/imputation.smk):
85    * Specify a conda environment or container for each rule.:
86      This way, the used software for each specific step is documented, and the
87      workflow can be executed on any machine without prerequisites.
88      Also see:
89      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
90      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
Formatting results
 1[DEBUG] 
 2[DEBUG] 
 3[DEBUG] 
 4[DEBUG] 
 5[DEBUG] 
 6[DEBUG] 
 7[DEBUG] In file "/tmp/tmpy8zaenw4/workflow/rules/reference.smk":  Formatted content is different from original
 8[INFO] 1 file(s) would be changed 😬
 9[INFO] 5 file(s) would be left unchanged 🎉
10
11snakefmt version: 0.11.5