coh_PMM_paper

Analysis scripts for L1 repeat activity in Plasmablastic Multiple Myeloma (PMM)

Project Overview

This repository contains code and analysis pipelines for the Plasmablastic Multiple Myeloma (PMM) project, focusing on the characterization of L1 repeat family activity using RNA-seq and whole-genome bisulfite sequencing (WGBS) data.

PMM is a high-risk subtype of multiple myeloma characterized by immature plasma cells (plasmablasts) in the bone marrow, showing aggressive behavior and reduced survival. These immature plasma cells display distinct morphological features, including a large nucleus, diffuse chromatin, and a prominent nucleolus.

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Data Summary

• Samples:

  • RNA-seq: PMM3, PMM4, PMM6, PMM7, PMM11, PMM14, PMM15, PMM16; BMPC1, BMPC2, BMPC3
  • WGBS: PMM1, PMM2, PMM3, PMM4, PMM6, PMM7, PMM9, PMM11, PMM12, PMM13, PMM14, PMM15, PMM16, PMM17, PMM18; B1_rest, B2_rest, B3_rest

• Genome build: hg38

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Pipeline Summary

RNA-seq Analysis

1. Preprocessing

   • Alignment: STAR
   • Indexing & sorting: samtools
   • Duplicate removal: picard

2. Gene counts

   • Quantification: STAR

3. Strand separation

   • Separate Watson and Crick strand reads: samtools

4. Visualization

   • Convert bam to BigWig: bamCoverage

5. Transposable Element (TE) transcripts

   • Called separately on Watson and Crick strands, with activation scores calculated using an in-house pipeline

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WGBS Analysis

1. Preprocessing and CpG DNA methylation calling

   • Quality control & trimming: trimGalore
   • Alignment: bismark (bowtie1)
   • Deduplication: picard
   • Methylation extraction: bismark_methylation_extractor
   • Coverage filtering: methylKit

2. Region calling

   • Quality control & trimming: trimGalore
   • Alignment: abismal
   • Deduplication & methylation extraction: DNMTools
   • Identification of PMD (partially methylated domains): DNMTools

3. INS analysis

   • Alignment: methylGrapher
   • Deduplication & methylation extraction: methylGrapher
   • INS supporting reads detection: in-house pipeline

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Repository Structure

The repository is organized as follows:

• /pipeline_scripts – Analysis pipelines
• /figure_scripts – Code for generating paper figures
• /R_shiny_web_app_scripts – Code for creating the R Shiny web app
• /conda_env_yml_files – YAML (.yml) files for creating conda environments

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How to Run

git clone https://github.com/QianhuiWan/coh_PMM_paper
# Change paths in the scripts to match your local data directory
# Install all required packages specified in the scripts
# Then run the pipeline scripts using `bash`:
bash /pipeline_scripts/*.sh

# Figures are generated using R version 4.4.1
# Run the figure scripts with `Rscript` after correcting the data paths
Rscript /figure_scripts/*.R

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License

This project is licensed under the MIT License.

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Citation

If you use the activation score pipeline in your study, please cite:

Qianhui Wan, Amy Leung, Mahek Vinod Bhandari, Hiroyuki Kato,
Joo Y. Song, Dustin E. Schones.
bioRxiv 2025.07.22.666173.
doi: 10.1101/2025.07.22.666173

• BibTeX format for this citation:

@article{wan2025activation,
  title        = {Methylation variability and LINE-1 activation in multiple myeloma},
  author       = {Wan, Qianhui and Leung, Amy and Bhandari, Mahek Vinod and Kato, Hiroyuki and Song, Joo Y. and Schones, Dustin E.},
  journal      = {bioRxiv},
  year         = {2025},
  publisher    = {Cold Spring Harbor Laboratory},
  doi          = {10.1101/2025.07.22.666173},
  url          = {https://doi.org/10.1101/2025.07.22.666173}
}

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Contact

For questions, please contact Qianhui Wan at qwan@coh.org.