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cca
clust
cor_bulk
cov
data
gene
gene_mean
gene_robust
heat
lib
qc
sample
var
zoom
.gitignore
README.md
index.Rmd
index.html

README.md

scM&T-Seq

Source code of the manuscript Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity (Nature Methods).

Abstract

We report scM&T–seq, a method for parallel single–cell genome–wide methylome and transcriptome sequencing, allowing discovery of associations between transcriptional and epigenetic variation. Profiling of 61 mouse embryonic stem cells confirmed known links between DNA methylation and transcription. Notably, the method reveals novel associations between heterogeneous methylation of distal regulatory elements and transcriptional heterogeneity of key pluripotency genes.

Content

  • /cca/: Canonical Correlation Analysis
  • /clust/: Clustering scM&T-Seq and scBS-Seq cells
  • /cov/: Coverage analysis
  • /cor_bulk/: Correlation scM&T-Seq methylation rates with bulk methylation rate
  • /data/: Data directory
  • index.Rmd: Table of content
  • /gene/: Gene-specific correlation analysis
  • /gene_mean/: Correlating mean methylation with gene expression
  • /gene_robust/: Robustness analysis gene-specific correlation
  • /heat/: Visualizing methylation and expression heatmap
  • /lib/: Library functions
  • /sample/: Sample-specific correlation analysis
  • /qc/: Quality control DNA methylation
  • /var/: Comparison methylation variability in context
  • /zoom/: Visualizing Esrrb gene

data/join/data.rds contains the pre-processed and joined methylation and expression data, which were used for the correlation analysis reported in the manuscript. The raw data and intermediate output files can be downloaded from GEO.

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