matthew_stone

Require diversity in the interview pool, not when making hiring decisions.

e.g. in a male majority profession, for every two male applicants selected to interview, select at least one female applicant. But once the candidate pool is established, pick the best available candidate for the job.

I bounced off Midnight’s Children the first time I tried to read it, but that was probably 10 or 15 years ago now. I’m in between books at the moment, so your comment will push me to put it on the top of my list for the new year :)

Girl, Woman, Other is one of my overall favorites from the last few years. Th character work is phenomenal. Do try to read a hard copy, rather than on an ereader, if you can. The book uses punctuation and the layout of text on a page creatively, and I’m not sure how well that gets preserved in an ebook.

Three Booker prize winners I’m particularly fond of:

The God of Small Things - Arundhati Roy

The Remains of the Day - Kazuo Ishiguro

Girl, Woman, Other - Bernardine Evaristo

Pachinko by Min Jin Lee is another recent literary favorite

It has been possible to print double-sided since at least Lion/2008…

100% agree, and it's wonderful to see Snakemake on the top of HN.

Snakemake is an invaluable tool in bioinformatics analysis. It's a testament to Johannes' talent and dedication that, even with the relatively limited resources of an academic developer, Snakemake has remained broadly useful and popular.

Super nice guy too, he's always been remarkably responsive and helpful. I saw him present on Snakemake back when he was a postdoc, and it really changed my approach to pipeline development.

Yes, it's a DSL.

Here's a simple scatter-gather example. Let's say you want to count the number of lines in each file for a list of samples, and report a table of counts collected from each sample. Define a rule to process each input file, and a rule to collect the results.

I find this much less complex than an equivalent bash workflow. Additionally, these rules can be easily containerized, the workflow can be parallelized, and the workflow is robust to interruption and the addition of new samples. Snakemake manages checking for existing files and running rules as necessary to create missing files, logic that is much more finicky to implement by hand in bash.

    with open('data/samples.txt') as slist:
        SAMPLES = [l.strip() for l in slist.readlines()]
    
    rule all:
        input:
            "results/line_counts.txt"
    
    rule count_lines:
        input:
            "data/lines/{sample}.txt"
        output:
            "processed/count_lines/{sample}.txt"
        shell:
            """
            cat {input} |
              wc -l | 
              paste <(echo -e {wildcards.sample}) - > {output}
            """
    
    rule collect_counts:
        input:
            expand("processed/count_lines/{sample}.txt", sample=SAMPLES)
        output:
            "results/line_counts.txt"
        shell:
            """
            cat <(echo -e "sample\tn_lines") {input} > {output}
            """

> I’d have directed an institute to run a report on theoretic safety and then a trial on volunteers.

Commonly known as “pre-clinical development” and “clinical trials”

High-risk populations such as the immunocompromised are tested in a Phase 4 trial.

> Once automated/easy/rapid sample prep comes, there will be mass adoption in the space.

Sounds like Elon calling biology a “software problem”.

Not saying that you’re wrong, just saying that the computational folk tend to discount the challenges and skills required in the wet lab.