Pipeline used for yeast coexp analysis

RNA-seq analysis

• rna_analysis/
  • read processing
    • alignment.sh
  • summarize read count data
    • merge_table.R
    • plot_raw_count_data.R
  • DE-seq2 analysis
    • plot_de_result.R
    • merge_de_result.R
    • sort_and_join.sh
    • (go_enrichment.R)

ChIP-seq analysis

• chip_analysis/
  • read processing
    • alignment.sh
  • peak calling
    • peak_calling.sh
    • extract_wt_peaks.sh
    • merge_all_peaks_dist.sh
  • coverage comparison
    • normalize.py
    • enrich_heatmap_ann.R
  • promoter coverage comparison
    • draw_lorenz_curve.R
    • (lorenz_curve.R)
  • diffbind analysis
    • raw_corr_diffbind.R
    • diffbind_comparison_tf.R

Co-expression cluster analysis

• coexp_analysis/
  • coexp_deg.R
    • extract the coexp clusters by dynamicTreeCut
    • input: coexp matrix from CoCoCoNet and output of DESeq2
  • coexp_enrichment.R
    • apply an enrichment analysis for each coexp cluster
    • input: output of coexp_deg.R and output of DESeq2

Reference

• Prevalent and Dynamic Binding of the Cell Cycle Checkpoint Kinase Rad53 to Gene Promoters.
  • Yi-Jun Sheu, Risa Karakida Kawaguchi, Jesse Gillis, Bruce Stillman.
  • bioRxiv 2021.05.23.445333; doi: https://doi.org/10.1101/2021.05.23.445333
  • eLife 11:e84320.