Really excited to post the first question in this forum. I have been browsing the topics for several days and finding a lot of useful information. My thanks to everyone making this such a resourceful place!
I am currently working with some illumina and 454 data generated from a viral genome that infects a eukaryote. The illumina reads I have are paired end reads. I am looking for an efficient way to assemble this virus genome. I ran all the illumina data through CLC genomic workbench for a test assembly. However, it generated a lot of contigs (about 3,000,00). Some of them are pretty big ranging from 84kb to 2kb. But most of them are small contigs of several hundred base pairs. A priliminary BLAST search revealed that a lot of these contigs probably originated from mitochondria/chloroplast, which means our sample had contamination from the host. I have checked several posts and looks like there is not an efficient way of assembling the data from different NGS platforms together. I have also found that students/scientists use Velvet and other free assembler softwares, which are pretty good.
My specific questions are:
1. What kind of workflow you recommend to assemble the data I have? Should I go for assembling the 454 and illumina data together, or assemble them separately? (Please provide some detailed information).
2. Which software (other than CLC or Seqman) do you recommend for the work? Velvet, Newbler....and so on..
3. How can I get rid of the reads that are actually contamination from the host? Other than BLASTing in NCBI, is there any particular tool to facilitate their elimination?
4. I believe the paired end information of illumina data will help me scaffolding once I finish the assembly. Do you think I am right? Is there any software that can use my assembled contigs and paired end information to scaffold them?
Sorry for such a long post, but I really need some help to clear up my confusion. Your inputs will definitely save me a lot of time and will help to avoid the pitfalls. I guess some of the members here have experience with working on NGS data of viruses. If they can share their advice, I will be really grateful.
And forgive my ‘not-so-scientific’ description of the problem…I am fairly new in the field! Ha ha.
I am currently working with some illumina and 454 data generated from a viral genome that infects a eukaryote. The illumina reads I have are paired end reads. I am looking for an efficient way to assemble this virus genome. I ran all the illumina data through CLC genomic workbench for a test assembly. However, it generated a lot of contigs (about 3,000,00). Some of them are pretty big ranging from 84kb to 2kb. But most of them are small contigs of several hundred base pairs. A priliminary BLAST search revealed that a lot of these contigs probably originated from mitochondria/chloroplast, which means our sample had contamination from the host. I have checked several posts and looks like there is not an efficient way of assembling the data from different NGS platforms together. I have also found that students/scientists use Velvet and other free assembler softwares, which are pretty good.
My specific questions are:
1. What kind of workflow you recommend to assemble the data I have? Should I go for assembling the 454 and illumina data together, or assemble them separately? (Please provide some detailed information).
2. Which software (other than CLC or Seqman) do you recommend for the work? Velvet, Newbler....and so on..
3. How can I get rid of the reads that are actually contamination from the host? Other than BLASTing in NCBI, is there any particular tool to facilitate their elimination?
4. I believe the paired end information of illumina data will help me scaffolding once I finish the assembly. Do you think I am right? Is there any software that can use my assembled contigs and paired end information to scaffold them?
Sorry for such a long post, but I really need some help to clear up my confusion. Your inputs will definitely save me a lot of time and will help to avoid the pitfalls. I guess some of the members here have experience with working on NGS data of viruses. If they can share their advice, I will be really grateful.
And forgive my ‘not-so-scientific’ description of the problem…I am fairly new in the field! Ha ha.
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