Michida et al., 2020
The number of transcription factors at an enhancer determines switch-like gene expression

Introduction

This repository contains the source code for the sequence analysis used in the above paper.

Relative paths under “src” are shown.

ATAC sequencing and genomic alignment

• Primary_analysis/ATAC-seq_mapping.sh

ChIP sequencing and genomic alignment

• Primary_analysis/ChIP-seq_mapping.sh

Single cell RNA sequencing and genomic alignment

• Primary_analysis/scRNA-seq_mapping.sh
• Primary_analysis/featureCounts.sh
• Fig2/SCDE.R

Identification of SEs and TEs

• Primary_analysis/Call_SE_TE.sh
• Fig1/Fig1A.R
• Fig1/Get_venn_num.sh
• Fig1/Fig1B.R
• Primary_analysis/Make_enhancer_catalog.sh
• Fig1/Fig1D.R

ATAC-seq coverage in SEs and TEs

• Sup_figs/SFig1D.sh
• Sup_figs/SFig1D.R

Quantification of ChIP and ATAC signals in enhancer and proximal TSS regions

• Primary_analysis/Make_bigwig.sh
• Primary_analysis/multiBigwigSummary.sh
• Fig1/Fig1C_E-H.R

Gene assignment to enhancers

• Fig2/Gene_assignment.R

Identification of RelA binding numbers from sequence data

• Primary_analysis/Peak_call_for_bulk.sh
• Fig3/Extend_bulk_ATAC_peaks.R
• Fig3/Get_RelA_peaks_in_ATAC_peaks.sh
• Fig3/RelA_peak_motif_count.R

Motif analysis

• Fig4/Fig4A-D.sh
• Fig4/Fig4E.R

Identification of NF-κB and PU.1 motifs

• Fig4/Peak_call_for_scATAC.sh
• Fig4/Extend_sc-ATAC_peaks.R
• Fig4/intersectBed_get_PU1_position_for_scATAC.sh
• Fig4/Count_RelA_PU1_overlap_for_scATAC.sh
• Fig4/Fig4E.R
• Fig5/Get_PU1_motifs_in_enhancers.sh
• Fig5/Get_RelA_PU1_overlap.sh
• Fig3/Get_NFkB_motifs_in_enhancers.sh
• Fig3/RelA_peak_motif_count.R
• Sup_figs/SFig6A.R

Gene Ontology (GO) analysis

• Sup_figs/SFig1A.R

Mathematical modeling

• Fig3/Filtering_genes.R
• Fig3/Fig3B_D.R
• Fig3/Fig3F.py
• Sup_figs/SFig4D.R
• Fig5/Fig5A-E.R

Prediction of single cell mRNA distribution using a mathematical model

• Fig3/Parameter_estimation.py

Authors

Hiroki Michida and Hiroaki Imoto

License

MIT