Illumina Metagenomics data

ssharma · 10-20-2010, 11:11 AM

Hi All,
I am new member to this forum.
Earlier i used to work with 454 data, now i am switching to illumina.
I am getting around 300 million reads (100bp) and its a metagenomic sample. So i am really confused about how to start my analysis.
Earlier i used approaches like blastx but now i think this is not a good option.
So i was just wondering if anyone had done something like this or have some idea on this.

I would really appreciate your help.

Thanks
SS

rwenang · 10-21-2010, 01:24 AM

Is it a 16S or WGS sample?

ssharma · 10-21-2010, 06:32 AM

Its a metagenomics environmental sample (no 16s).

themerlin · 10-21-2010, 08:11 AM

The real question is....what's the question? Are you looking for specific genes, or want to take an inventory of all genes?

Have you tried assembling the reads yet? That's always a little sketchy with mixed communities, but it might be a good place to start.

ssharma · 10-21-2010, 08:45 AM

thanks for your input themerlin,
Actually mainly its going to be a community study (in nut shell i need to annotate all of the sequences)
Yes i tried assembly but it doesn't look good, but yes i will try again with different programs.

kmewis · 12-01-2010, 12:36 PM

Is this just sequence data from DNA straight from the environment, or did you clone it into vectors first?

I handle metagenomics data, we do it in fosmids though, so it's easy to assemble contigs from one fosmid (phred/phrap). Trying to do the whole environment at once will likely be tougher. Once I have contigs, we use blastx to looks for homology and tools like fgenesb to find ORFs.

Dilipmohana · 12-02-2010, 02:42 AM

hi i am new to this site can anyone tell me about effective working in schrodinger plz pass useful video tutorials if possible,

greigite · 12-05-2010, 12:35 PM

Take a look at MG-RAST for annotation of your data http://metagenomics.nmpdr.org.

Quote:

Originally Posted by ssharma

Hi All,
I am new member to this forum.
Earlier i used to work with 454 data, now i am switching to illumina.
I am getting around 300 million reads (100bp) and its a metagenomic sample. So i am really confused about how to start my analysis.
Earlier i used approaches like blastx but now i think this is not a good option.
So i was just wondering if anyone had done something like this or have some idea on this.

I would really appreciate your help.

Thanks
SS

Eric · 12-10-2010, 09:00 AM

Hi,

What do you mean by "annotate" ? Are you looking at "who is there" or "what are the functions" ?
Do you have reference genomes at hand, or genomes of organisms close to the ones in your sample ? Do you have an idea of the complexity of the population ? Is it eukaryote or microbes, or both ?
You can consider first trying to have an idea of the composition of your population, looking at some marker genes (eg : trying to find 16S or 18S reads in your dataset by mapping against reference databases)
If you have known reference genomes, you can also map reads against them, to evaluate the complexity/diversity
For a first glimpse at functions, you can try UniRef50 or KEGG genes (or any other functionally classified reference protein set) as a proxy.

gridbird · 12-21-2011, 10:22 AM

You can try WebMGA: http://weizhong-lab.ucsd.edu/metagenomic-analysis/

colindaven · 03-30-2012, 06:03 AM

You can try approaches like
-de novo assembly (metaVelvet, Abyss etc)
-fast clustering - (CD-Hit, RAMMCAP)
-reference based alignment (Genometa)

faozhi · 04-04-2012, 10:09 PM

I would trim the reads (based on qual and remove adapters), then start assembling.
If you would like to know who are there, you could use MG-RAST or just blastn your trimmed reads against greengenes or SILVA 16S databases.

seb567 · 04-05-2012, 12:55 PM

Quote:

Originally Posted by ssharma

Hi All,
I am new member to this forum.
Earlier i used to work with 454 data, now i am switching to illumina.
I am getting around 300 million reads (100bp) and its a metagenomic sample. So i am really confused about how to start my analysis.
Earlier i used approaches like blastx but now i think this is not a good option.
So i was just wondering if anyone had done something like this or have some idea on this.

I would really appreciate your help.

Thanks
SS

You can reduce the volume of data by doing a de novo assembly.

HTML Code:

mpiexec -n 64 Ray \
 -k \
 31 \
 -p \
 Sample/ERR011142_1.fastq.gz \
 Sample/ERR011142_2.fastq.gz \
 -p \
 Sample/ERR011143_1.fastq.gz \
 Sample/ERR011143_2.fastq.gz \
 -o \
 Assembly

Sébastien Boisvert

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10-20-2010, 11:11 AM	#1
ssharma Member Location: Georgia Join Date: Oct 2010 Posts: 19	Illumina Metagenomics data Hi All, I am new member to this forum. Earlier i used to work with 454 data, now i am switching to illumina. I am getting around 300 million reads (100bp) and its a metagenomic sample. So i am really confused about how to start my analysis. Earlier i used approaches like blastx but now i think this is not a good option. So i was just wondering if anyone had done something like this or have some idea on this. I would really appreciate your help. Thanks SS

10-21-2010, 01:24 AM	#2
rwenang Member Location: Singapore Join Date: Jan 2009 Posts: 31	Is it a 16S or WGS sample?

10-21-2010, 06:32 AM	#3
ssharma Member Location: Georgia Join Date: Oct 2010 Posts: 19	Its a metagenomics environmental sample (no 16s).

10-21-2010, 08:11 AM	#4
themerlin Member Location: Flagstaff, AZ Join Date: Feb 2010 Posts: 51	The real question is....what's the question? Are you looking for specific genes, or want to take an inventory of all genes? Have you tried assembling the reads yet? That's always a little sketchy with mixed communities, but it might be a good place to start.

10-21-2010, 08:45 AM	#5
ssharma Member Location: Georgia Join Date: Oct 2010 Posts: 19	thanks for your input themerlin, Actually mainly its going to be a community study (in nut shell i need to annotate all of the sequences) Yes i tried assembly but it doesn't look good, but yes i will try again with different programs.

12-01-2010, 12:36 PM	#6
kmewis Junior Member Location: BC Join Date: Sep 2010 Posts: 7	Is this just sequence data from DNA straight from the environment, or did you clone it into vectors first? I handle metagenomics data, we do it in fosmids though, so it's easy to assemble contigs from one fosmid (phred/phrap). Trying to do the whole environment at once will likely be tougher. Once I have contigs, we use blastx to looks for homology and tools like fgenesb to find ORFs.

12-02-2010, 02:42 AM	#7
Dilipmohana Junior Member Location: India, Chennai Join Date: Nov 2010 Posts: 2	hi i am new to this site can anyone tell me about effective working in schrodinger plz pass useful video tutorials if possible,

12-10-2010, 09:00 AM	#9
Eric Junior Member Location: Paris Join Date: Oct 2009 Posts: 1	Hi, What do you mean by "annotate" ? Are you looking at "who is there" or "what are the functions" ? Do you have reference genomes at hand, or genomes of organisms close to the ones in your sample ? Do you have an idea of the complexity of the population ? Is it eukaryote or microbes, or both ? You can consider first trying to have an idea of the composition of your population, looking at some marker genes (eg : trying to find 16S or 18S reads in your dataset by mapping against reference databases) If you have known reference genomes, you can also map reads against them, to evaluate the complexity/diversity For a first glimpse at functions, you can try UniRef50 or KEGG genes (or any other functionally classified reference protein set) as a proxy.

12-21-2011, 10:22 AM	#10
gridbird Member Location: san diego Join Date: Oct 2010 Posts: 16	You can try WebMGA: http://weizhong-lab.ucsd.edu/metagenomic-analysis/

03-30-2012, 06:03 AM	#11
colindaven Senior Member Location: Germany Join Date: Oct 2008 Posts: 415	You can try approaches like -de novo assembly (metaVelvet, Abyss etc) -fast clustering - (CD-Hit, RAMMCAP) -reference based alignment (Genometa)

04-04-2012, 10:09 PM	#12
faozhi Junior Member Location: Australia Join Date: Dec 2011 Posts: 5	I would trim the reads (based on qual and remove adapters), then start assembling. If you would like to know who are there, you could use MG-RAST or just blastn your trimmed reads against greengenes or SILVA 16S databases.