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To disagree, I'm a computational biologist and it's my firm belief 99% of the scientifically important stuff happens before the stats and plotting. That's not to say I dismiss those things and haven't done my fair share of stats, but just that the difference between real results and incorrect results most often happens before that step.

I'm a microbiologist though, for stuff like human RNA-Seq I understand that it's often plug and play to get a gene counts table at this point.




Sure, but I think, for example, representation learning, doesn’t involve manipulating an array of strings.


>To disagree, I'm a computational biologist and it's my firm belief 99% of the scientifically important stuff happens before the stats and plotting.

I'm a microbiologist too, but the kind that uses mostly off-the-shelf tools to do the taxonomic/functional assignment on metagenomes, and then stats/data science on the features. I kinda didn't know what you mean by "99% of the scientifically important stuff happens before the stats and the plotting".

I mean, give me a 500x2.6x10^6 sparse matrix of gene function abundances and tell me that you've done anything scientifically meaningful. Or on the other side, let me hand you a fastq file from sequencing a poorly extracted DNA sample, and you give me the best algorithm in the world, and there's nothing scientifically meaningful that's going to come out of that.




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