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rrmm

Data analysis scripts for scRNA-seq analysis of relapsed and refractory multiple myeloma

https://github.com/rippelab/rrmm

Science Score: 62.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    DOI references
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    Academic publication links
    Links to: ncbi.nlm.nih.gov
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    Academic email domains
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    Institutional organization owner
    Organization rippelab has institutional domain (malone.bioquant.uni-heidelberg.de)
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    Scientific vocabulary similarity
    Low similarity (6.6%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Data analysis scripts for scRNA-seq analysis of relapsed and refractory multiple myeloma

Basic Info
  • Host: GitHub
  • Owner: RippeLab
  • Language: HTML
  • Default Branch: main
  • Homepage:
  • Size: 20.8 MB
Statistics
  • Stars: 9
  • Watchers: 1
  • Forks: 2
  • Open Issues: 0
  • Releases: 1
Created over 5 years ago · Last pushed over 4 years ago
Metadata Files
Readme Citation

README.md

Nextflow data processing pipelines and R code for single cell RNA sequencing analysis of relapsed and refractory multiple myeloma

The RRMM (relapsed and refractory multiple myeloma) repository contains Nextflow data processing pipelines and R code for single cell RNA sequencing (scRNA-seq) analysis. The code was used in the study "Subclone-specific microenvironmental impact and drug responses in refractory multiple myeloma revealed by single cell transcriptomics" by Stephan M. Tirier, Jan-Philipp Mallm, Simon Steiger, Alexandra M. Poos, Mohamed H. S. Awwad, Nicola Giesen, Nicola Casiraghi, Hana Susak, Katharina Bauer, Anja Baumann, Lukas John, Anja Seckinger, Dirk Hose, Carsten Müller-Tidow, Hartmut Goldschmidt, Oliver Stegle, Michael Hundemer, Niels Weinhold, Marc S. Raab and Karsten Rippe.
Plots for main and supplementary figures of the study can be created with the R-scripts provided in the RRMM project and the data available at accession number GSE161801 of Gene Expression Omnibus .

Figures

Contains R markdown notebooks to recreate figures from the above study.

RRMM samples and scRNA-seq dataset

scRNA-seq analysis of RRMM tumor cells

Treatment response of +1q subclones

Analysis of cellular interaction of myeloma and BME cells

T-cell heterogeneity in RRMM patient vs. healthy donor samples

CD16+ monocyte heterogeneity in RRMM

BME changes in +1q RRMM

Processing Pipeline

Contains templates for the Nextflow pipeline to conduct the following tasks: - Preprocessing, qc and cell type annotation with scrublet and SingleR - Create a summary table and a merged object of the final processed file - Identification of tumor subclones from the scRNA-seq data with InferCNV - Prediction of interactions between different cell types with CellPhoneDB

Owner

  • Name: RippeLab
  • Login: RippeLab
  • Kind: organization
  • Location: Heidelberg

Citation (citation.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: Steiger
    given-names: Simon
    orcid: https://orcid.org/0000-0002-4845-5042
  - family-names: Tirier
    given-names: Stephan
    orcid: https://orcid.org/0000-0002-7249-6194
  - family-names: Rippe
    given-names: Karsten
    orcid: https://orcid.org/0000-0001-9951-9395
title: "Nextflow data processing pipelines and R code for single cell RNA sequencing analysis of relapsed and refractory multiple myeloma."
version: v1.0
date-released: 2021-09-27
doi: 10.5281/zenodo.5532552
url: "https://github.com/RippeLab/RRMM/"

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