StergachisLab/IsoSeq_smk

Pipeline for MAS-Seq processing

Overview

Topics:

Latest release: v.1.0, Last update: 2025-04-11

Linting: linting: failed, Formatting: formatting: failed

Deployment

Step 1: Install Snakemake and Snakedeploy

Snakemake and Snakedeploy are best installed via the Mamba package manager (a drop-in replacement for conda). If you have neither Conda nor Mamba, it is recommended to install Miniforge. More details regarding Mamba can be found here.

When using Mamba, run

mamba create -c conda-forge -c bioconda --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

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/StergachisLab/IsoSeq_smk . --tag v.1.0

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 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.

config.yaml Documentation

This file configures input files, sample metadata, and reference genome paths. Please use absolute paths in this file.

Configuration Options

1. individuals

Defines sample information, including phased VCF files and long-read sequencing data. Condition labels are pre-established.

Structure:

individuals:
  <individual_id>:
    deepvariant_vcf: <path_to_vcf_file>
    <condition_name>:
      <label_id>:
        - <path_to_flnc_bam_file>

2. reference_genome

Path to the reference genome FASTA file.

reference_genome: <path_to_fasta_file>

3. pigeon_annot

Path to the GTF annotation file used for transcript annotation. Some tools like pigeon classify require a pre-indexed annotation file. To index, please try manually creating the .pgi index before running the pipeline.

pigeon index test_data/gtf/gencode.v46.annotation.gtf

pigeon_annot: <path_to_gencode_gtf_file>

4. docs_dir

Path to the supporting isoranker documents. Template uses docs nested inside our main IsoSeq_smk pipeline, with the relative path just above workflow. Feel free to specify an absolute path where your files are stored. File extensions do matter, please ensure all files have the proper extensions prior to submission.

docs_dir: "../docs"

5. threads

Number of CPU threads to use for processing.

threads: <num_threads>

Example:

individuals:
  ind_1:
    deepvariant_vcf: /path/to/vcf/deepvariant_phased_ind_1.vcf.gz
    untreated:
      label_A:
        - /path/to/flnc/ind_1/condition1/IsoSeqX.flnc.bam
    treated:
      label_B:
        - /path/to/flnc/ind_1/condition2/IsoSeqX.flnc.bam
  ind_2:
    deepvariant_vcf: /path/to/vcf/indiv_2.haplotagged.vcf.gz
    untreated:
      label_A:
        - /path/to/flnc/ind_2/condition1/IsoSeqX.flnc1.bam
        - /path/to/flnc/ind_2/condition1/IsoSeqX.flnc2.bam
        - /path/to/flnc/ind_2/condition1/IsoSeqX.flnc3.bam
    treated:
      label_B:
        - /path/to/flnc/ind_2/condition2/IsoSeqX.flnc.bam
reference_genome: /path/to/fasta/genome/hg38.fa
pigeon_annot: /path/to/reference_annotfile/gencode.v46.annotation.gtf
docs_dir: "../docs"
threads: 8

Linting and formatting

Linting results

Using workflow specific profile workflow/profiles/default for setting default command line arguments.
KeyError in file /tmp/tmpvlibm3tl/StergachisLab-IsoSeq_smk-36c6662/workflow/Snakefile, line 9:
'individuals'
  File "/tmp/tmpvlibm3tl/StergachisLab-IsoSeq_smk-36c6662/workflow/Snakefile", line 9, in <module>

Formatting results

[DEBUG] 
[DEBUG] 
[DEBUG] In file "/tmp/tmpvlibm3tl/StergachisLab-IsoSeq_smk-36c6662/workflow/Snakefile":  Formatted content is different from original
[INFO] 1 file(s) would be changed 😬
[INFO] 1 file(s) would be left unchanged 🎉

snakefmt version: 0.10.2