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LieberInstitute / brain-epigenomics

https://jhubiostatistics.shinyapps.io/wgbsExprs/
MIT License
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dna-methylation rna-seq rstats

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brain-epigenomics

DOI

Located in JHPCE at /dcl01/lieber/ajaffe/lab/brain-epigenomics

This repository contains the code used in the analyses in the following citation:

Price AJ *, Collado-Torres L *, Ivanov NA, Xia W, Burke EE, Shin JH, Tao R, Ma L, Jia Y, Hyde TM, Kleinman JE, Weinberger DR, Jaffe AE †. Divergent neuronal DNA methylation patterns across human cortical development reveal critical periods and a unique role of CpH methylation. Genome Biology. 2019. DOI: 10.1186/s13059-019-1805-1. Pre-print: bioRxiv, 2018. DOI: 10.1101/428391.

If you use anything from this repository please cite the above. Here's a bibtex entry:

@article{price_divergent_2019,
    title = {Divergent neuronal {DNA} methylation patterns across human cortical development reveal critical periods and a unique role of {CpH} methylation},
    volume = {20},
    issn = {1474-760X},
    url = {https://doi.org/10.1186/s13059-019-1805-1},
    doi = {10.1186/s13059-019-1805-1},
    abstract = {DNA methylation (DNAm) is a critical regulator of both development and cellular identity and shows unique patterns in neurons. To better characterize maturational changes in DNAm patterns in these cells, we profile the DNAm landscape at single-base resolution across the first two decades of human neocortical development in NeuN+ neurons using whole-genome bisulfite sequencing and compare them to non-neurons (primarily glia) and prenatal homogenate cortex.},
    number = {1},
    urldate = {2019-09-26},
    journal = {Genome Biology},
    author = {Price, Amanda J. and Collado-Torres, Leonardo and Ivanov, Nikolay A. and Xia, Wei and Burke, Emily E. and Shin, Joo Heon and Tao, Ran and Ma, Liang and Jia, Yankai and Hyde, Thomas M. and Kleinman, Joel E. and Weinberger, Daniel R. and Jaffe, Andrew E.},
    month = sep,
    year = {2019},
    pages = {196}
}

The raw data is publicly available through the PsychENCODE Consortium Knowledge Portal at DOI: 10.7303/syn5842535.

License Attribution-NonCommercial: CC BY-NC This license lets others remix, tweak, and build upon our work non-commercially as long as they acknowledge our work.

Annotation of the included files:

Directory Description
brainseq_pipeline processing the homogenate RNA-seq data. Uses the LIBD RNA-seq pipeline developed by EE Burke, L Collado-Torres, and AE Jaffe.
BSobj_subsets subsetting the BSSeq objects based on differential methylation at individual cytosines
bsseq creating the BSSeq objects used in later analyses
bumphunting identifying and visualizing differentially methylated regions of CpGs
CREs identifying, exploring and visualizing DNA methylation features like UMRs, LMRs, etc.
DMR exploring and visualizing the DMRs by cell type, age, and the interaction between cell type and age
DMR_acf assessing the autocorrelation of methylation between neighboring cytosines within the DMRs
homogenate_RNA explore RNA-seq from homogenate DLPFC
lambda check the lambda spike-in of the whole genome bisulfite sequencing samples
meth_vs_expr analysis of the relationship between cytosine methylation levels, splicing and gene expression
misc miscellanious analysis including global methylation patterns
non-CpG exploration and visualization of non-CpG methylation patterns
psi calculate the "percent spliced in" of splicing variants in homogenate RNA-seq data
PWMEnrich explore enrichment for canonical splice donor and acceptor sequences and transcription factors
single_CpGs analyzing single CpGs, including comparing to Lister et al (Science, 2013) data and comparing detection of age effects in homogenate and cell type-specific samples and deconvolution of neuronal subtypes
sorted_nuclear_RNA analyzing the sorted neuronal (NeuN+) and glial (NeuN-) nuclear RNAseq samples
README.md README file for the github repository