https://github.com/brocklab/cmduo-analysis

https://github.com/brocklab/cmduo-analysis

Science Score: 26.0%

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

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
  • DOI references
    Found 2 DOI reference(s) in README
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (8.1%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: brocklab
  • Language: R
  • Default Branch: main
  • Size: 7 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme

README.md

This repo contains all code to reproduce analysis and figures in "Mapping cell-cell fusion at single-cell resolution" (https://doi.org/10.1101/2024.12.11.627873)

Accessing raw data

Raw and processed single cell RNA-sequencing can be downloaded from GEO with accession number GSE286213. Targeted barcode sequencing to generate a list of barcodes in the samples using pycashier can be downloaded from Gene Expression Omnibus (GEO) with accession number GSE286212.

In notebooks 7-13, the h1806_colors_cellclass_hclust_nb-barassigned_ccclustered_precc_singlets.rds is equivalent to GSE286213_CMDuo_seurat_qc_barcodeAnnotated_HCC1806_samples.rds from GEO, and mb231_colors_cellclass_hclust_nb-barassigned_ccclustered_precc_singlets.rds is equivalent to GSE286213_CMDuo_seurat_qc_barcodeAnnotated_MDAMB231_samples.rds. Start here if you want to perform downstream analysis. These objects can also be used as the starting point in notebooks 3-6, the objects in notebooks 1-2 need to be built from raw.

Raw data processing

To start from raw sequencing data, follow the notes in 00_Raw_data_processing_and_alignment_notes.md

Setting up the Rstudio analysis environment

To setup your analysis environment, download the Docker Image which is equipped to launch Rstudio with all the necessary packages and versions: docker pull phdidi/cmduo_rocker:latest

Port Rstudio to your local browser from your server by running: docker run --rm -ti -e PASSWORD=makeapassword -e USERID="$(id -u)" -e GROUPID="$(id -g)" -p 8770:8787 -v "$(pwd)":/home/rstudio/workspace cmduo_rocker

On your local machine run (change 'user' to your username on your server and 'host' to your server name) ssh -NL 8770:localhost:8770 -p 22 user@host

Then open a browser and navigate to: http://localhost:8770/⁠

When prompted, enter 'rstudio' as your username and 'makeapassword' (or whatever you set this to) as your password to launch Rstudio.

Owner

  • Name: brocklab
  • Login: brocklab
  • Kind: organization
  • Location: Austin, TX

GitHub Events

Total
  • Push event: 1
  • Public event: 1
Last Year
  • Push event: 1
  • Public event: 1