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Code for the empty droplet and cell detection project from the HCA Hackathon.

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Distinguishing empty and cell-containing droplets

Overview

This repository contains analysis scripts and simulation code for the manuscript Distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data by Lun et al. (2018). It also contains the manuscript files themselves, which can be compiled with pdflatex if you're into that sort of thing.

Downloading files

Enter data and run:

  • download_tenx.sh, which will download publicly available data from the 10X Genomics website.
  • download_placenta.sh, which will download unprocessed 10X data from the Vento-Tormo et al. study.

Simulations

Enter simulations and run:

  • simrun.R, which will perform simulations based on the real datasets to assess cell detection methods.
  • plotsim.R, to recreate the plots in the manuscript for the simulation results.

Real data

Enter real and run:

  • realrun.R, which will apply cell detection methods to the real datasets.
  • negcheck.R, which will examine the p-value distribution reported for low-count barcodes.

Each subdirectory of analysis contains self-contained analysis files for each data set. Run:

  • analysis.Rmd, which will perform the analysis of each dataset.
  • plot_maker.R, which will create the plots used in the manuscript.

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Code for the empty droplet and cell detection project from the HCA Hackathon.

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