Case study · ATAC-seq
How does androgen (DHT) stimulation reshape the open-chromatin landscape of prostate cancer cells, and can the driving transcription factor be identified from accessibility alone?
Two questions. First, how a single dose of androgen (dihydrotestosterone) remodels the open-chromatin landscape of an androgen-driven prostate cancer line. Second, whether the transcription factor responsible for that remodelling can be read straight off the ATAC-seq data, without needing a matched RNA-seq experiment.
End-to-end ATAC-seq workflow on 4 samples (VCaP, vehicle vs 1 nM DHT, 2 replicates each): adapter trimming, Bowtie2 alignment, mitochondrial and ENCODE-blacklist filtering, MACS3 peak calling, and ENCODE-standard quality control (TSS enrichment, fragment-size periodicity, FRiP, library complexity). A fixed-width reproducible consensus peak set then fed three layers of analysis: differential accessibility with DiffBind (DESeq2), per-transcription-factor motif activity with chromVAR, and base-resolution footprinting with TOBIAS, all against the JASPAR2024 motif set. Differentially accessible peaks were annotated to their nearest gene.
ATAC-seq is often delivered as a peak list and little else. The value here is the interpretation: three independent views of the same data converging on one answer, the androgen receptor programme, written into the open chromatin and named without any expression data. The report states that conclusion in plain English, flags the one honest caveat (AR shares its DNA motif with the glucocorticoid and progesterone receptors, so the family co-ranks), and keeps every number traceable to an auditable pipeline. This is the kind of regulatory-biology question, which transcription factor is driving the change, that ATAC-seq answers better than expression alone.
The actual client deliverable layout — same files, same structure, same format.
Fixed-fee, 7–10 business days. Email with your omics type + sample count and a quote comes back within 2 business days.