Major waves of H2A.Z incorporation during mouse oogenesis and preimplantation embryo development

A collection of scripts used for manuscript: Major waves of H2A.Z incorporation during mouse oogenesis and preimplantation embryo development.
Link to the manuscript: https://www.nature.com/articles/s41467-025-66919-x

Table of contents

File	Figure	Description
fluorescenceBoxplots.R	1e	Signal intensity visualization of H2A.Z immunofluorescence in oocytes.
peaks_PCA.R	1g	PCA of oocyte and early embryo stage H2A.Z peaks.
plotAnnoPie.R	1f	Draws pie charts of genomic feature annotation distributions of all H2A.Z peaks.
H2AZbubbleplots.Rmd	2c	R Markdown generating bubble plots for overlap between TSS clusters and oocyte embryonic gene categories.
LADbubbleplots.Rmd	3c	R Markdown generating bubble plots for overlap between LADS and all H2A.Z peaks.
plotAnnoClust.R	3f	Genomic feature annotation and visualization of H2A.Z peak clusters .
peaks_go.R	3g	GO term enrichment analysis on H2A.Z peak clusters.
peaks_go_heatmap.R	3g	Generates a heatmap summarizing GO term enrichment results.
TEbubbleplots.Rmd	4b & S5a	R Markdown for generating bubble plots for overlap between transposable elements and non-TSS/CGI H2A.Z peaks.
z-score_plot.R	S1c	Computes and plots z-score distributions of H2A.Z signal at TSSs.
CorrelationMatrices.R	S1f, S2a, S2b & S2d	Computes and visualizes pairwise correlation matrices between H2A.Z data from this study and published studies.

Required R Packages

To run the analysis and visualization scripts in this repository, the following R packages must be installed:

Category	Packages
Data manipulation & plotting	tidyverse, ggpubr, ggrepel, gridExtra, plot3D, corrplot
Statistical analysis	rstatix
Functional enrichment	gprofiler2
Genomic annotation & visualization	ChIPseeker, GenomicRanges, TxDb.Mmusculus.UCSC.mm10.knownGene, ComplexHeatmap
Data import	readxl

Usage

git clone https://github.com/lerdruplab/H2A.Z.git
cd H2A.Z

Installation of R packages:

You can install all required packages with the following commands in R:

# CRAN packages
install.packages(c(
  "tidyverse", "readxl", "rstatix", "plot3D",
  "ggrepel", "gprofiler2", "ggpubr",
  "gridExtra", "corrplot"
))

# Bioconductor packages
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install(c(
  "ComplexHeatmap", "ChIPseeker",
  "TxDb.Mmusculus.UCSC.mm10.knownGene",
  "GenomicRanges"
))

Easy installation of R packages by creating a conda environment (Recommended):

Executing the command below in terminal will create a conda environment with all the required R packages.

conda create -n h2az_lerdrup \
  r-base=4.3.3 r-tidyverse r-lintr r-languageserver r-devtools nodejs \
  r-readxl r-rstatix r-plot3d r-ggrepel r-gprofiler2 r-ggpubr r-gridextra \
  bioconductor-complexheatmap bioconductor-chipseeker \
  bioconductor-txdb.mmusculus.ucsc.mm10.knowngene \
  bioconda::bioconductor-genomicranges

Activate the environment before running any scripts:

conda activate h2az_lerdrup

Contact

If you encounter any difficulties running the scripts, please open a new issue in the Issues section of the repository.