Bit

Prank War

Imagine this. You’re blind folded, at half-court, during halftime at a University of Maryland basketball game, setting yourself up for a shot potentially worth $500,00 in front of thousands of screaming fans.

But, you’re also in the midst of an ongoing—at times vicious and ever escalating—prank war with your best friend at work, which happens to be College Humor (an internet comedy website since rebranded “Dropout”).

This is the real premise of installment #7 of the prank war between Amir Blumenfeld (prankee) and Streeter Seidell (pranker), which took place in 2009. Trust me it’s worth a watch.

If want to see one of the ways that Amir got Streeter (installment #4 of the prank war) and are able to tolerate—what could be a fatal dose of secondhand cringe—you may want to also check out Seidell’s laugh-less standup comedy set.

Base Pair

Low-pass Whole Genome Sequencing

If you are a venture capitalist, I’d imagine seeing “1X” would make you sick to your stomach. However, if you are a bioinformatician, you are not in the business of “10X” returns on investment.

Rather, you are interested in getting your hands on high-throughput, cost-effective genetic sequencing—paired with high quality clinical phenotypes and outcomes.

Standard whole genome sequencing (WGS) typically targets ~30X depth—meaning on average each base pair in the genome is covered.

For WGS, the genome is broken down into small pieces for short reads. These short reads—which are about 150 base pairs in length—are aligned to a reference genome by software programs to re-construct the genome. This is because it’s not yet feasible to sequence an entire chromosome all at once since they range from 50 million to 300 million base pairs in length!

While cost for WGS has drastically decreased over time—$2.7 billion to fund the completion of the first human WGS in 2003 to less than $1500 today—cost is still a concern.

However, instead of genotyping arrays being the only cheaper, now there’s a new player—enter low-pass WGS (also called “low-coverage WGS”). Low-pass WGS is defined as having a sequencing depth of 1X or less.

To learn more about low-pass WGS compared to genotyping arrays and how it can increase statistical power for genome-wide association studies, I recommend checking out the article “Low-pass sequencing increases the power of GWAS…” by Li et al published in Genome Research (2021).

Thank you for reading and have a fulfilling weekend!

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