Assay of Transposase Accessible Chromatin sequencing (ATAC-seq) is widely used in studying chromatin biology, but a comprehensive review of the analysis tools has not been completed yet. Here, we discuss the major steps in ATAC-seq data analysis, including pre-analysis (quality check and alignment), core analysis (peak calling), and advanced analysis (peak differential analysis and annotation, motif enrichment, footprinting, and nucleosome position analysis). We also review the reconstruction of transcriptional regulatory networks with multiomics data and highlight the current challenges of each step. Finally, we describe the potential of single-cell ATAC-seq and highlight the necessity of developing ATAC-seq specific analysis tools to obtain biologically meaningful insights.

Despite an increase in survival for children with acute lymphoblastic leukemia (ALL), the outcome after relapse is poor. To understand the genetic events that contribute to relapse and chemoresistance and identify novel targets of therapy, 3 high-throughput assays were used to identify genetic and epigenetic changes at relapse. Using matched diagnosis/ relapse bone marrow samples from children with relapsed B-precursor ALL, we evaluated gene expression, copy number abnormalities (CNAs), and DNA methylation. Gene expression analysis revealed a signature of differentially expressed genes from diagnosis to relapse that is different for early (< 36 months) and late (> 36 months) relapse. CNA analysis discovered CNAs that were shared at diagnosis and relapse and others that were new lesions acquired at relapse. DNA methylation analysis found increased promoter methylation at relapse. There were many genetic alterations that evolved from diagnosis to relapse, and in some cases these genes had previously been associated

BackgroundThe Illumina HumanMethylation450 BeadChip (HM450K) measures the DNA methylation of 485,512 CpGs in the human genome. The technology relies on hybridization of genomic fragments to probes on the chip. However, certain genomic factors may compromise the ability to measure methylation using the array such as single nucleotide polymorphisms (SNPs), small insertions and deletions (INDELs), repetitive DNA, and regions with reduced genomic complexity. Currently, there is no clear method or pipeline for determining which of the probes on the HM450K bead array should be retained for subsequent analysis in light of these issues.ResultsWe comprehensively assessed the effects of SNPs, INDELs, repeats and bisulfite induced reduced genomic complexity by comparing HM450K bead array results with whole genome bisulfite sequencing. We determined which CpG probes provided accurate or noisy signals. From this, we derived a set of high-quality probes that provide unadulterated measurements of DNA methylation.ConclusionsOur method significantly reduces the risk of false discoveries when using the HM450K bead array, while maximising the power of the array to detect methylation status genome-wide. Additionally, we demonstrate the utility of our method through extraction of biologically relevant epigenetic changes in prostate cancer.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-51) contains supplementary material, which is available to authorized users.