[Nomijill]

CLC bio Support

Please, whenever you have questions about the behavior of the CLC bio assemblers, contact [email protected]. You may also be interested in trying the new version of the assembler, if you have not already. The new algorithm scaffolds the paired end information.

[sklages]

I am currently assembling about 215 gigabases of sequence data with clc_novo_assemble. Should I expect clc_novo_assemble to print its progress while it is running? Its last output of progress (80%) was two days ago.

what does CLC support tell you? They are usually very helpful and responsive.

[lmilne]

I am currently assembling about 215 gigabases of sequence data with clc_novo_assemble. Should I expect clc_novo_assemble to print its progress while it is running? Its last output of progress (80%) was two days ago.

[Nomijill]

hi, björn
I totally agree with you that CLC is good at CPU and RAM control. But, i just wondering that why it doesn't support scaffolding which is important for genome assembly.

BTW, could you please tell me what is the region with highest information gain? Now i am just trim the reads randomly. But, i am thinking to use a sliding window to scan the region with less homopolymer(for example, the length of the homopolymer is < 4).

Just for everyone who is using the Genomics Workbench to know - There have been numerous updates to the functionality. Much of which is available as a plug-in download. For the de novo assembler there are two significant changes. 1 - The assembler now supports scaffolding of paired-end reads. 2 - You now have the ability to change the k-mer value as one of your parameters.

Happy Sequencing :-)
Naomi

[usad]

Hi

just the most unambigous region. So if your whole 454 read aligns to one region and one region only to search for a short region in the read which also would allow placing it at this position only and not on another contig and use this as a pseudo-Illumina read.
But it probably doesn't help too much it will jut give you a few more links. (Maybe simulate first what you can expect, based on your N50 /aveage length or length distribution, linker length quality and number)

Cheers,
Björn

[shaohua.fan]

Did you do random trimming or did you trim them down to the region with the highest information gain (which is what we do).

I think it had large genomes in mind. It is really good in RAM consumption and quite ok in thread usage and thus speed. Maybe CLC4 brings some scaffold capabilities?

Cheers,
björn

hi, björn
I totally agree with you that CLC is good at CPU and RAM control. But, i just wondering that why it doesn't support scaffolding which is important for genome assembly.

BTW, could you please tell me what is the region with highest information gain? Now i am just trim the reads randomly. But, i am thinking to use a sliding window to scan the region with less homopolymer(for example, the length of the homopolymer is < 4).

[usad]

Did you do random trimming or did you trim them down to the region with the highest information gain (which is what we do).

I think it had large genomes in mind. It is really good in RAM consumption and quite ok in thread usage and thus speed. Maybe CLC4 brings some scaffold capabilities?

Cheers,
björn

[shaohua.fan]

I didn't know you have 454 data. So what kind of data do you have?

if it is 99% illumina and a bit for 454 scaffolding:
I reckon also SSPACE can be beaten into submission by giving it fake reads. It works with SOAP at least you could plainmail Tbolger if you wanted to give that a shot. Or better yet switch to an assembler/scaffolfer that takes all data into account. (I guess that was why you asked the question in the first place :-))


Cheers,
björn

i have tried to trim the long 454 reads (20K PE) to 36 and 72 bp and fed them as Illumina reads to SSPACE. But the scaffolding quality didn't improve much.

The reason I asked the question to CLC people is that we bought the CLC since it appears an all in one package (de novo genome assembly with hybrid 454 and illumina data). But, the scaffolding function, which is essential for a complicated genome assembly, is not included. I guess CLC is expecting all their customs buy the CLC then de novo assembly the virus or simple bacterial genome?

[usad]

I didn't know you have 454 data. So what kind of data do you have?

if it is 99% illumina and a bit for 454 scaffolding:
I reckon also SSPACE can be beaten into submission by giving it fake reads. It works with SOAP at least you could plainmail Tbolger if you wanted to give that a shot. Or better yet switch to an assembler/scaffolfer that takes all data into account. (I guess that was why you asked the question in the first place :-))


Cheers,
björn

[shaohua.fan]

No idea,
I guess the easiest way to help yourself is using SSPACE, after you got your contigs with CLC.

Cheers,
björn

but SSPACE does not support scaffolding using the 454 reads.

[usad]

No idea,
I guess the easiest way to help yourself is using SSPACE, after you got your contigs with CLC.

Cheers,
björn

[shaohua.fan]

hi, CLC people,

I have a question about CLC genomic workbench that when will CLC add the scaffolding option in the genome assembly. Until the latest version (version 4.7.2), CLC genomic workbench still does not support this. But, this is of important for the genome assembly.

Thanx

[Abishai3911]

Hi,

I am basically a molecular biologist/biochemist and not a Bioinformatician. However, I have been trying to use CLC Genomics Workbench to analyze my 454 data resulting from PCR amplicons. I was able to import the .fna and .qual file into CLC. Now when I do use the "Map reads to reference" under "Highthroughput sequencing" for my sequencing reads (containing 121000 sequences of 310bases) with a 32bp reference sequence, the matched sequences that it shows is incorrect. For eg I am getting only 97 matches instead of atleast 10000 matches that are expected. Also, sometimes when the reference sequence is shorter for example 15 bp, then it says the match count is zero and that there are zero matches.

Can somebody help me with this? Am I doing the mapping correctly?

Thanks in advance.

JAG

[NextGenSeq]

We don't have the assembly cell but on a computer with 16GB of RAM and 24 GB of data it would take about 6 hours. I've assembled 250 million reads from a HiSeq in ~16 hours. This if for reference assembly. However, de novo assembly takes about the same time.

[sklages]

Does anyone have an idea how long it takes to perform a single end assembly with CLC assembly cell 3.2.2. on 24 Gbases of data using quadcore with 16 GB or RAM.

P.S. I know what they claim on the company website, I just like to hear about experiences of an unbiased user...

There is probably no correct answer. It may depend on organism, type of library, type of sequence data, quality of sequence data, size of target (genome,transcriptome), type of processors, speed of IO etc. And, .. 16GB of RAM is not too much ... :-)

Let us know when your assembly has finished and how the quality is ..

Sven