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There's also CLC Genomics Workbench (although it is a commercial package).
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Yes, CLC Genomics Workbench will use all three data types. I use the program on Windows. However you will need lots of RAM. For my files/genomes I needed 32GB (the max we could put into my box). If you work with small bacterial genomes and simple transcriptomes you maybe able get away with 8GB RAM (the minimal requirement for CLC Workbench)
MartaComment
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I am using the CLC Genomics Workbench on my laptop running XP with 3 GB and it handle up to about 10 million Illumina reads in a de novo assembly, but things larger than that causes problems on my small machine. So it seems you can work with smaller bacterial genomes on less than 8 GB of ram, at least that is my experience.Originally posted by Marta View PostComment
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Stegger, thanks! Is is nice to know that CLC Workbench can run on a 3GB machine. How long are your 10M reads?Comment
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Their 36 bases.Comment
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Sciguy, I notice that you last updated your list in August. Are there any significant changes since then? Or am I wrong about the reading of the update?Comment
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It's definitely been updated since...when I use my superpowers to edit the first post, it doesn't show the date.Originally posted by Nomijill View Post
The data @ http://wiki.seqanswers.com is probably a bit more current as it's being maintained by the community rather than just sciguy and myself!Comment
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I'm guessing we need some kind of wiki forum ... but I not sure what form... um?
I think the problem is that the wiki is so bad for threaded conversations, we need a place to discuss the wiki...
For each software package that is in the wiki, I have added a link to search the forum for that package. This is only a small step. Generally I'm not sure how to more tightly integrate the two different approaches.Comment
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good thing thanksComment
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nice work!Comment
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Locking this thread for now, as the wiki is easier to maintain and this thread seems to have outlived its usefulness.
If you have a question about a specific package...and have already searched for the answer, please start a new thread about it.Comment
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Love 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.07-01-2026, 11:43 AM
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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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