Hello, I have a question regarding computer settings.
The lab I belong to is currently in the process of setting up microbiome research, and is experiencing difficulties in purchasing a computer needed for BI analysis.
Qiime2 analysis was performed by installing a virtual machine on a Windows computer with 16GB of RAM, (in VirtualBox, 10GB) but the use of DADA2, Classifier was limited due to lack of performance, and that steps were able to be taken with the cooperation of other research institutes.
I am currently planning to purchase a computer with suitable specifications (planning to set up a mac or Linux system), and I would like to ask if I can get any recommendations or specifications.
I am also considering purchasing a computer for personal investment(for BI analysis), so I am also considering a laptop such as below. (The cost is under consideration at around $ 2,000 or less.)
Macbook Pro 13, M2, RAM 24GB
DELL Inspiron 16 DN5620-UB05KR, i7, RAM 32GB
DELL Inspiron 14 DN5420-UB02KR, i5, RAM 32GB
HP Elitebook 650 G9-4W5J8AV, i5, RAM 64GB
However, Mac's M chip has been pointed out about the disadvantages of long-term use due to compatibility issues compared to intel, and I would like to ask for advice on this. Which laptop is best to buy and use?
And as considered above, as a personal computer, I'm considering using a laptop because the desktop would be inconvenient. Our laboratory does not have a server, so analysis using a server is expected to be limited.
I would be very grateful if you could give me some advice on these difficulties.
Before you read my answer, I would like to point that it is only my opinion and nothing more, so it is really up to you to choose a best option for you .
In that case, if it possible to get a laptop with 64 Gb of RAM, I would go for it. Usually 32 GB is enough for a lot of the tasks, but not for all of them and in that case a higher RAM is crucial, especially if server is not easily available.
Also, it is quite convenient to have 2 ssd - one for wnidows and one for linux.
I'll also weigh in, because I have opinions , but they're also my opinions.
I like a Mac Book, personally. I've been working on a 16GB macbook for years and do pretty well with 16S analyses. (I bought a 13" a couple years ago as a work/personal computer before I started a recent job.) I feel like the M1 chip does a decent job allocating memory and I haven't had any performance issues. (I do occasionally leave my computer to "cook" overnight, but I put an oven rack underneath so it stays cool ).
I'm also not computationally savy enough to work between two OS. I like the fact that my Mac has a unix backend and I can do a lot of Unix stuff, but I can also get microsoft word/adobe which I need personally and professionally. It's a more integrated experience for me.
You might also look at something like EC2 or Azure if you have big computing projects. It will save your machine and might be easier to bill (I have burned out laptops.) If you configure it correctly, you can use it as a pop up server: run DADA2, train your classifier, and do beta diversity on the server and then pull your files down locally for visualization and analysis.
Thank you for your kind reply.
It seems that RAM performance is also important.
In fact, I have a Windows laptop that I have been using for a long time, so I plan to use this laptop only by setting it to the Linux system for analysis.
When that is planned, I wonder if it would be better to focus on a computer with good RAM specifications as you said.
I will take your advice and make a good purchase. thank you very much!
Thank you for your detailed answer!
Mac's M2 chip is definitely coveted.
I have a lot of worries because the visualization package developers I love also use Macs.
What made me thinking is the price difference, the 24GB Mac Pro is about $700 to $800 more expensive than the 64GB hp laptop.
Still, considering the excellent performance of the M-chip, I think it would be wiser to buy a MacBook.
It seems really difficult to know which computer to buy.
When setting up Linux on HP and running a little heavy analysis, it is difficult to predict whether heat or fan sound will be severe.