Originally posted by jimmybee
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I have to second waiting for the 10.9.1 release at minimum. Often times Apple gets that out inside a month.Originally posted by mcnelson.phd View PostThe AppNap and compressed memory features in particular seem like they could give those systems a boost and help extend their usable life span.
Also, are you running out of RAM? Do you have 96GB installed? I can't imagine that this whole compressed memory thing does much good for serious work. Maybe it saves the OS a GB or 2 for lightly used things that load up in RAM, but in general, if you need stuff in RAM, why would you want it compressed? Then you have to uncompress and recompress it upon every use? If that's how you cram something that needs 128GB into 96GB, its going to be painfully slow. And I don't think that's even what it is doing. This is probably a feature for machines with <8GB of RAM....
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We're currently OK with RAM usage and capacity, and my intention wasn't that compressed memory would allow us to analyze a larger dataset than the system is capable of handling.Originally posted by Wallysb01 View PostAlso, are you running out of RAM? Do you have 96GB installed? I can't imagine that this whole compressed memory thing does much good for serious work. Maybe it saves the OS a GB or 2 for lightly used things that load up in RAM, but in general, if you need stuff in RAM, why would you want it compressed? Then you have to uncompress and recompress it upon every use? If that's how you cram something that needs 128GB into 96GB, its going to be painfully slow. And I don't think that's even what it is doing. This is probably a feature for machines with <8GB of RAM....
My main line of thought was that compressed memory and AppNap would help keep systems like our iMacs, which are used for light analyses by multiple users, to last longer between hardware replacements. Basically, these systems are used for small genome assemblies, light 16S analysis, Sanger sequence analysis, etc. along with basic things like using MS Office doing statistical analyses. Because most users would have multiple programs open as they work on and analyze their data, something like AppNap could help extend the usable lifespan of these systems so we don't have to buy a whole new system every year or two.
For heavier analyses we would rely on our linux clusters, so we're not trying to skimp on our computing capabilities.
And as I thought when I first posted, it looks like I'm better off waiting to see what happens with the first few point updates to stabilize the OS. I've also heard from some colleagues that some older applications that they and we use are no longer supported, so we'll have to look at whether or not we still need them and if it's worth paying for upgrades or if something else is available that we might try instead.
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by GATTACATLove this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
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07-01-2026, 11:43 AM -
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by SEQadmin2
I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.
Here are nine questions we think about, in roughly the order they matter, before...-
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