Scripts and analysis approaches for ATAC-Me origin data
Most scripts assume access to a high power computer or cluster computing environment
- 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_loop.sh
- trim.slrm
- mapping_loop_walt.sh
- mapping_walt.slrm
- StandardATAC_Bowtie_Loop.sh
- StandardATAC_Bowtie.slrm
- methpipe_loop.sh
- methpipe.slrm
- macs2_loop.sh
- peak_filtering.txt
ATAC-Me vs. Standard ATAC Read Count Correlation
- read_count_correlation.txt
Allelic Methylation Analysis
- allelic_methylation_comparison.R
TC-seq Processing and Clustering
DNA methylation Heatmaps Across TCseq Cluster Regions
- TCseq_cluster_meth_heatmaps.txt
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
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
Boxplot Time Series for Extended Time Point Data
- Extended_Timepoints_Boxplot_Comparision.R