ATAC-seq best practices (tips)

Figure 3. Signal features generated by different methods for profiling chromatin accessibility.

A few best practices for ATAC-seq assays are suggested as follows:

  • Digest away background DNA (medium/dead cells) using DNase I22
  • Use fresh/cyropreserved cells/tissues to isolate nuclei7,9
  • Reduce mitochondrial/chloroplast DNA contamination as much as possible by using the Omni-ATAC protocol or other methods22–25
  • Optimize the ratio of the amount of Tn5 enzyme to the number of nuclei
  • Optimize the number of PCR cycles19
  • Perform Paired-end (PE) sequencing, e.g., 2 x 50 to 100 bp
  • Sequence > 50 M PE reads (~200 M for footprinting analysis)7

A few best practices for ATAC-seq data analysis are suggested as follows:

  • Perform raw read QC using FASTQC before alignment
  • Perform post-alignment QC using ATACSeqQC10
  • Perform peak calling using a peak caller, such as MACS226 in narrowdPeak mode with option settings: “shift -s and extend 2s”, Genrich, or HMMRATAC.27
  • Perform post-peak calling QC
    • Annotate peaks and generate peak distribution among genomic features using ChIPpeakAnno28
    • Obtain functions of genes associated to peaks using the Genomic Regions Enrichment of Annotations Tool (GREAT)29

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New position at the University of Iowa

I am very excited to have begun a new position this July as a Bioinformatics Specialist within the Iowa Institute for Human Genetics (IIHG).

I am fortunate to be working  with a very talented team of expert bioinformaticians, researchers, and programmers.   I have a lot to learn about my new field, but I’m enthusiastic about the challenge and looking forward to participating in the fast-moving and cutting-edge research at the nexus of computer science, data analysis, genetics, and biology.