234 karma · joined December 1, 2020
You heard it here first folks, close your memory positions Q2 2027 at the latest to avoid getting caught flat-footed when prices drop.
Like others have said you need to switch to employment mode, and finding a job is your full-time job
I can't say I'm overly fond of Baez's definition, but far be it from me to question someone of his stature.
Unreliable casualty numbers aside, Russia simply has way more men, and can eventually attrite Ukraine into a demographic death spiral. Indeed, with the exodus of ~20% of its population since the start of the war, this demographic trajectory may now be inexorable. Eastern Ukraine, where much of the most fertile land is, and where most of the fighting has occurred, is now likely littered with bomb parts and unexploded ordinances, and the prospect of the jackals of the American arms industry turning it into a live weapons laboratory is particularly grim.
GRCh38 - chr2:41785474-41785474
or something like that.
You will need to align your FASTQ to one of these reference genomes using a short-read aligner such as BWA-MEM (assuming your genome was sequenced using something like Illumina NGS) to produce a BAM (binary alignment map) file, and then from there use a variant calling tool such as GATK's HaplotypeCaller or Google's DeepVariant to produce a VCF (variant call format) file, which will contain the mutations in your genome. Then you can see if any of the mutations found in your genome match those in ClinVar.
As humans are diploid, you will also need to be cognizant of the zygosity of each mutation, i.e., whether you have a particular mutation on just one of your two chromosomal homologs (heterozygote) or both (homozygous mutant), as this may affect whether or not the mutation is of concern, the variant caller will attempt to determine this for you and report it in the VCF file.
Short-read sequencing data is a notoriously bad datatype for reconstructing the low-complexity / repetitive regions of genomes, so up until recently the most commonly used reference genomes have left many of these regions "dark". According to the preprint, the Y chromosome has the highest density of these low-complexity regions. It's also something of a bioinformatic nuisance when constructing a generic human reference genome, as it's only present in 50% of the population.
So a 4x speedup? A completely irrelevant performance improvement for a "quantum computer".
In any case it's a pretty silly contrivance, how about the oil age? or the silicon age? Both of those are likely to remain more impactful than the LK-99 age, in the event that it does turn out to be an ambient temp/pressure superconductor.