ATAC-Me

Scripts and analysis approaches for ATAC-Me origin data

Most scripts assume access to a high power computer or cluster computing environment

Software

- bedtools v2.26.0
- samtools 1.5
- deeptools 3.1.2
- STAR_2.6.1a 
- WALT v1.0 
- bowtie2 version 2.2.6 
- FastQC v0.11.4
- cutadapt 1.8.3 
- trim_galore 0.4.0 
- DeSeq2 1.18.1 (R version 3.4.3)
- ChIPeeker 1.14.2 (R version 3.4.3)
- clusterProfiler 3.6.0 (R version 3.4.3)
- bagfoot 0.9.6 (R version 3.4.3)

General Processing Scripts

Trimming

- trimming_loop.sh
- trim.slrm

Mapping

- mapping_loop_walt.sh
- mapping_walt.slrm
- StandardATAC_Bowtie_Loop.sh
- StandardATAC_Bowtie.slrm

Methylation levels

- methpipe_loop.sh
- methpipe.slrm

Peak calling

- macs2_loop.sh
- peak_filtering.txt

Figure 1

ATAC-Me vs. Standard ATAC Read Count Correlation

- read_count_correlation.txt

Allelic Methylation Analysis

- allelic_methylation_comparison.R

Figure 2

TC-seq Processing and Clustering

- TCseq_Analysis.R

Figure 3

DNA methylation Heatmaps Across TCseq Cluster Regions

- TCseq_cluster_meth_heatmaps.txt

Figure 4

KEGG Pathway/GO Analysis of Dynamic ATAC Peak Neighboring Genes

K-means Clustering of RNA-seq Differential Genes

- DEseq2_RNA_Timecourse.R

Hierarchical Clustering of Top Variable Genes Near Dynamic ATAC Peaks + Methylation

- topVariable_Genes_Heatmap.R 

Figure 5

Scatterplot Correlations of ATAC vs. RNA and Methylation vs. RNA

- Correlation_Scatterplot_ATAC_RNA_Meth.R

Boxplot Time Series Integrating ATAC, RNA, Methylation

- Integrative_Boxplot_TimeSeries.R

Figure 6

Boxplot Time Series for Extended Time Point Data

- Extended_Timepoints_Boxplot_Comparision.R