Yeah, they'll take a while to get generated.
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Hi... now 24 hours are passed and indexing is still running on my MAc (see previous post of this thread). What can I do now? My processor is dual core... I have to insert an option into the command line to take into account that processor has 2 core?
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simobioinfo is indexing GRCh37/human. If bandwidth is not a problem then you can download the preformatted bundle (sequence, indexes and annotations) from this link: http://support.illumina.com/sequenci...e/igenome.html
@simobioinfo: This is the sort of thing I was trying to warn you about in terms of user experience.
@Devon: If you have indexes for that known to work on a Mac you could post them for simobioinfo.
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How much RAM does this Mac have? If you look at my previous post you'll see where I said that if you don't have enough RAM it will take very, very long to build in the index. To build the human genome you probably need 5-6GB but you will have to monitor RAM usage as the index is building to know for sure. And it doesn't matter how many cores you have Bowtie2-build is a single process.Originally posted by simobioinfo View PostHi... now 24 hours are passed and indexing is still running on my MAc (see previous post of this thread). What can I do now? My processor is dual core... I have to insert an option into the command line to take into account that processor has 2 core?
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My mac has 4Gb of RAM. I suppose that it could be enough to build index. I don't know how to check ram usage.Originally posted by biocomputer View PostHow much RAM does this Mac have? If you look at my previous post you'll see where I said that if you don't have enough RAM it will take very, very long to build in the index. To build the human genome you probably need 5-6GB but you will have to monitor RAM usage as the index is building to know for sure. And it doesn't matter how many cores you have Bowtie2-build is a single process.
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I was able to build the index on another machine and use it on my macbook pro with 3 gigs of RAM. I really wouldn't recommend doing this on a machine with that little RAM as you end up swapping all the time. Since you have more RAM than my old laptop, hopefully you'll get better performance. I'll post the indices later today and send you a link.
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Researchers using sequencing and genomics tools often have to make trade-offs. They can choose between speed or scale, short reads or long-range information, or targeted panels or a view of the whole transcriptome. New technologies that have been released this year are built to address those tough choices.
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