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  • #31
    In my honest opinion if you are doing biomedical research and you don't have bioinformaticians around and you are not planning to create a whole department it would be better to go for commercial software.
    I am a bioinformatician and processing data from let's say RNAseq, DNAseq and ChIPseq would need three different analysis pipelines that even taking into account that you will be using open source existing tools it takes a loooooot of work and time to get everything ready and efficiently working.

    About learning the command line, everybody can learn the command line, but you will also need after learning the time to do the work. It is not a thing of a couple of minutes even for a command line ninja. I agree anyway that it will be no bad practice to get a bit into the command line.

    There it goes an example of commercial software doing the work for RNAseq and ChIPseq: https://www.integromics.com/products/genomics/ngs/.
    No command line and publication ready figures. But this suits for a particular case you will have to find the one for your precise case.

    (Don't blame for the ad, yes I work for this enterprise, but I think it is really a constructive example for this discussion)

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    • #32
      It was inevitable that the commercial software vendors would recommend their own tools on this thread. If I want to go commercial, why do I want to pay Integromics and also pay Spotfire for this? Spotfire has never been able to deal with data of NGS size and the fact that Integromics is adding an additional layer of expense is extremely unattractive.

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      • #33
        It was not my intention to make of this a discussion about Integromics or Spotfire software, it was just an example to justify the use of commercial software for a biomedical researcher with no bioinformatics expertise. And obviously this is the case that I best know.

        I will just say about your critics that we use Spotfire for results visualization, which is OK. I don't know if Spotfire deals or not with NGS data but we do. We are not loading a 20GB BAM file into the Spotfire...

        Coming back to the main topic I am still of the opinion that for a researcher with no bioinformatics expertise at hand, it will be cheaper, considering that time is money, to go for the commercial software.

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        • #34
          As a taxpayer

          I work for a commercial company, and our software is compared to Galaxy all the time, and we are glad that Galaxy and other publicly available tools are creating software. It drives us and other commercial companies to be better. Therefore, even the users of commercial software benefit from the government spending. Commercial products have to be a lot better than the free products in order to compete. Otherwise, why would someone pay for something they can get for free.

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          • #35
            Galaxy is a fine piece of software but it is lacking in certain aspects when it comes to analyzing NGS data.

            How about an alternative approach?
            Nowadays there are a lot of pipeline workflow programs that covers NGS analyzing.
            The interesting concept is that...
            1 Biologist produce the data
            2 Bioinformaticians create a pipeline which they share (or some other knowledgeable scientist)
            3 Biologist just utilizes the shared pipeline for their analysis

            At the moment there are also people who share their pipelines in a variety of software.
            Software is in this area come from both the commercial side and freeware side
            Suggestions....

            Taverna http://www.taverna.org.uk Freeware
            KNIME http://www.knime.org/ mostly freeware (HPC version costs)
            pipeline pilot http://accelrys.com/products/pipeline-pilot/ commercial

            I would suggest a closer look at KNIME. A software which is free for your desktop to play around with and has some NGS tools
            Leverage an ever-growing library of extensions, join the global community, contribute to data-driven innovation.


            Taverna seems a bit immature as a product compared to KNIME, and Pipeline Pilot costs a lot

            Or does anyone have other suggestions?
            Last edited by MenzZana; 01-31-2013, 11:40 AM.

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            • #36
              On the same line of inguiries, there is a commercial product which seems promising
              namely DNANexus.



              That perhaps could answer you questions.
              Perhaps someone around here has some prior experience with it

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              • #37
                Originally posted by dnart View Post
                I don't think you are getting it. I am not going to learn command line programming, instead I am going to focus on learning more biology. The question was whether it is more cost effective to hire a bioinformaticist (~$75k/year) or buy commercial software (~5k/year).
                I've mentioned this before, but you will have a lot of trouble getting reliable, repeatable results out of any software without a bioinformaticist. It requires a bit of computer / maths / biology knowledge in order to interpret the results and understand what results are real, and what results are due to other factors (e.g. input data garbage, covariates, normalisation methods, etc.).

                If you're going to focus completely on biology, your choice is basically between a) hiring a bioinformaticist and giving them a minimal budget for spending on software and computing capability and b) hiring a bioinformaticist and giving them a large budget for spending on software and computing capability -- maybe more like $75k/year + $2k/year vs $65k/year + $10k/year.
                Last edited by gringer; 02-06-2013, 08:41 PM.

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                • #38
                  Very interesting thread. From my perspective, as a bioinformatician, is that commercial bioinformatics software lags well behind the leading edge. If you are doing research and your questions contain bioinformatics challenges, then you can't use commercial software - you need bioinformaticians to talk with and/or to build you an appropriate solution. However, as certain analysis techniques get reduced to common practice commercial tools do a good job in packaging this in an easy to use manner.

                  For example, ten years ago even research bioinformaticians were only just feeling their way through the complexities of microarray analysis and commercial analysis tools produced garbage. Now that the complexities of microarray analysis are better understood, the commercial tools do a very good job and it would take quite a skilled bioinformatician to replicate their results.

                  I think with most applications of NGS we are still in the learning phase. Some of the commercial tools do an okay job for certain analyses. However, for many NGS applications, even the cutting edge command-line tools still produce dubious results and in this case you are probably better served with experienced bioinformatician who knows the pitfalls.

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