Avadis NGS vs CLC Genomics?

[gringer]

These softwares are supposed to be made for people with no prior knowledge of bioinformatics, or at least so does the companies behind it claim, but nope. They talk about the algorithms and explain them in a way so that a biologist like me gets lost half the way (this is especially true about the Avadis). And when you finally have passed the aligning step, it needs a whole education to understand and interpret your results.

For someone to use the high-cost commercial bioinformatics suites effectively (where by high-cost, I mean similar in cost to a bioinformatician's salary), they need very similar skills to what would be required to run low-cost (or FOSS) programs with similar effectiveness.

The programs are not particularly easy to use for complete novices, and not customisable enough that a bioinformatician would be able to set things up so that they are easy to use. Therefore, use of these programs needs substantial amounts of hand-holding by someone with fairly advanced knowledge of bioinformatics (i.e. you would need a double-bioinformatician salary for running these programs).

Given that researchers will typically want to try a few things that haven't been done before, I find it doubtful that a software suite could be designed that will work for almost everyone.

[steven]

Originally Posted by NGSfan

Biology will eventually turn into an information science and if you want to do research you will have to use computers.
Harsh words but this is coming from someone like you who started as a biologist and fought his way into bioinformatics. It's not easy, but for your own career I would strongly urge you to learn - otherwise you will be forever dependent on others to do your analysis - and that means you will be waiting.

I strongly disagree with this.

Biology is an experimental science. The fact that you are a fan of biotechnology and computers -as many of us by the way- does not reduce biology to NGS data analysis. How self centred is this!

Although I also started as a biologist and became a bioinformatician, I do not pretend everyone has to do the same. Either you have infinite learning capacities -good for you then- or you just cannot be an expert in everything. At some point you have to choose. Of course the best is to learn and know about everything, but that is simply not possible in real life. Absolute independence is pure utopia. Unless you work alone in your lab, chances are you will always depend on some collaborator at some point, whether it is to collect samples, set up an experiment, write or review an article, use a machine, take pictures, export the data, get a grant.. why should this become a major issue when it comes to analyzing the data?

Look at it the other way around: as a bioinformatician, I am 100% dependent on biologists to generate some interesting data, and I am fine with that. I won't come back to the bench to try running the experiment myself simply because I am "waiting". First I prefer to have it done by an expert. Second I am never "waiting". To use your words, if a project involves that many people are just "waiting" at some point maybe it shouldn't have been given the funding..

[NGSfan]

Originally Posted by steven

I strongly disagree with this.

Biology is an experimental science. The fact that you are a fan of biotechnology and computers -as many of us by the way- does not reduce biology to NGS data analysis. How self centred is this!

I am a biologist by training first. I know and understand everything from beginning (the molecular biology of sample prep) to the end (computational analysis). My graduate school training emphasized that I learn BOTH in order to be competitive and competent.

Analytical chemists and experimental physicists also do experimental science but do you think they just hand off the data from their experiment to another "computational" person to analyze for them? Why is it that biologists think they can get away with just knowing the molecular biology and biochemistry and not understand the computational analysis? (And vice-versa - bioinformaticians that don't have a clue about the biology and treat the data no different than any other data and are completely oblivious to biases in molecular biology sample preps!)

Originally Posted by steven

Although I also started as a biologist and became a bioinformatician, I do not pretend everyone has to do the same. Either you have infinite learning capacities -good for you then- or you just cannot be an expert in everything. At some point you have to choose. Of course the best is to learn and know about everything, but that is simply not possible in real life. Absolute independence is pure utopia. Unless you work alone in your lab, chances are you will always depend on some collaborator at some point, whether it is to collect samples, set up an experiment, write or review an article, use a machine, take pictures, export the data, get a grant.. why should this become a major issue when it comes to analyzing the data?

OK maybe I come across as arrogant. It is not about "thumping one's chest" and declaring they are master of the universe. But you should strive to know as much as you can and at the very least - be competent enough to analyze your own data!! It's fine if someone does the BLAST for you or the BWA alignment for you - but the expectation , in my experience , has been that all the analysis and interpretation is to done by the bioinformatican. The biologist see it as "just pushing a button".. yet they take for granted the effort it takes to make sure there are low false positives in those results.

This is a typical problem in biologist - bioinformatician collaborations.

I ask you this - If you are just producing the data and handing it off to someone else to analyze for you, who should get the first authorship on the paper? In my opinion the data producer is just a technician... amirite?

There are plenty of grad students and postdocs out there demanding they get first authorship for spending 6 months to produce the data, but cannot analyze it themselves! Is that not ridiculous? How can you call yourself a scientist if you cannot analyze and interpret the data? or know the quality of your data?

Originally Posted by steven

Look at it the other way around: as a bioinformatician, I am 100% dependent on biologists to generate some interesting data, and I am fine with that. I won't come back to the bench to try running the experiment myself simply because I am "waiting". First I prefer to have it done by an expert. Second I am never "waiting". To use your words, if a project involves that many people are just "waiting" at some point maybe it shouldn't have been given the funding..

What if the experiment doesn't work, and you think you can trust the "expert". Often the "expert" is a technician or a grad student... maybe a postdoc doing a new protocol for the first time. How would you know what questions to ask if something goes wrong if you don't know the molecular biology behind the sample preparation and don't have experience doing PCR / ligations / etc ??

I'm sorry but maybe my training was very demanding and in my circles to just throw up your hands and say "well I'm not a biologist / bioinformatician don't ask me" was seen as an excuse that was not acceptable.

[mathew]

After seeing the ad of Avadis NGS on Seqanswer page I tried to use its trial version but they never send an email- either their system is messed up or they just advertise. Then I came to know from couple of my colleagues that they either did not get any sort of trial of this tool (no email) form last 2-3 months. I am not sure then why they advertise, unless they are willing to check their system

Thanks

[Buzz0r]

FYI, Illumina already launched their own cloud solution called BaseSpace. It includes many 3rd party softwares and is opening up completely by the end of the year. Might be worth checking it out!

http://blog.basespace.illumina.com/

Cheers...

[rfilbert]

Hi All,

Well I have finished evaluating these 4 options for analysis of NGS data and I decided to go with Partek Flow. The reasons:

1. For Galaxy, you really need to be a certified bioinformaticist to know how to use it - this is not a tool for a biologist like myself.
2. CLC is expensive, and does not have the downstream analysis capabilities that AVADIS or Partek have.
3. AVADIS has too many bugs. I just could not get my analysis done.
4. Partek Flow was the most user friendly software I've ever seen and their sales and technical support team were also far better than the others.

YMMV
Best,
Robert

[mathew]

I will vote for Galaxy as it is very user friendly and provide you the control on your analysis to certain extent not just a black box. If one invest some time one can get into through adjustment of various parameters. I have seen over time that it is always risky to follow blindly a commercial tool.... It is simply too risky.
My thoughts only

[rfilbert]

I have used Galaxy and I have used Partek Flow, and in my opinion Partek Flow is much easier to install and use than Galaxy. It uses both Partek algorithms and open source (e.g. Bowtie/Tophat, BWA, GATK, etc.) but somehow runs them faster than Galaxy. It also has a lot that Galaxy lacks, such as controlled vocabularies, outstanding graphics, etc. For example, I couldn't do the downstream analysis needed for my RNA-Seq study in Galaxy. They also have a dedicated technical support team I can call for help. I'm not sure what you mean by "blindly following a commercial tool"? What is the difference between that and blindly following Galaxy?

[gringer]

Has anyone used Galaxy for NGS analysis from a high-throughput illumina sequencer? I would expect that the browser-based system would choke on the 50-200GiB BAM files that would be produced from a 200-1000M read run.

[rfilbert]

Both Partek Flow and Galaxy are browser based. Being browser based means they both are client/server architectures. It is the server that would need to choke on large data, not the browser. So it depends on the server hardware and how efficiently each system utilizes that hardware. As I mentioned, I have used both for fairly large studies and Flow ran the same aligners significantly faster than Galaxy.

[simonandrews]

It's unlikely that the underlying aligner would have run at different speeds on different systems since they're both going to be calling out to the same code. It seems more likely that the aligners were run with different parameters (different levels of multi-threading, different alignment stringencies etc) which can have a big effect on how long they take to process their data.

[rfilbert]

No, I ran them with the exact same parameters.

[cement_head]

I think that CLC GW is pretty good - we've had it hear for over a year.

[prathima]

Strand NGS (Formerly Avadis NGS) is an integrated platform that provides analysis, management and visualization tools for next-generation sequencing data. It supports extensive workflows for alignment, RNA-Seq, small RNA-Seq, DNA-Seq, Methyl-Seq, MeDIP-Seq, and ChIP-Seq experiments.
Pipeline manager option can be used to streamline large scale analysis.

More details on various enhancements/features can be found at http://www.strand-ngs.com/features

[Strandlife]

Strand NGS has improved a lot. The user interface is similar to that of Agilent Technologies GeneSpring, since it is built on same platform Avadis. Strand NGS is very flexible, since its interface auto-adopts to experiment type, only showing relevant analysis steps and functions (i.e guided workflows). You can also customize via R scripts and Jython scripts. Annotation Manager provides access to annotations from within the tool and many more