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In my view, it’s time to slow down and or even “pause” AI development. The tech has progressed exponentially in just the last year, and shows no sign of slowing down or reaching a plateau. As a result, it is outpacing our ability to understand, align, and adapt to it. I signed the Future of Life Institute letter six months ago.

This editorial in the Hill.com makes the case:

Six months later, our call to slow AI development is more crucial than ever

Right now, tens of thousands of brand-new cutting-edge chips are humming away in massive river-cooled data centers, growing the next generation of artificial minds. We don’t know what their powers will be, how they will think or make decisions or how to robustly align them to human interests. But they will be more capable than most people at many things, and more capable than the finest human minds at some things. 
We have a rapidly-closing window of opportunity to take control of this process, as a species, before the runaway development of AI takes control of us. We must use it.

ANTHONY AGUIRRE, OPINION CONTRIBUTOR – 09/22/23 8:30 AM ET

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 nuclei^7,9
  
• Reduce mitochondrial/chloroplast DNA contamination as much as possible by using the Omni-ATAC protocol or other methods^22–25
  
• 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

Copied From: https://haibol2016.github.io/ATACseqQCWorkshop/articles/ATACseqQC_workshop.html

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.