One thing you could do is to make your own. MetaSim is one package for this, but there are others, I'm sure. It allows you to set up a number of genome sequences and create a simulated set of sequence reads from a mixture of the genomes in known proportion.

Thanks Jonathan.

Maybe I did not make myself clear. Here I mean real sequenced data. For example, a bacteria community with know organisms is sequenced.

Actually I used a simulator (grinder) to generate my own. The concern I had is that whether the simulated data is similar enough to the real sequencing data.

Ah I see. We have done this with synthetic mixed viral populations but not bacterial. It seems like it's something that someone would have needed to do as a control to demonstrate the effectiveness of their latest metagenomics toolkit...

We may want to check this article, they did exactly what you ask for: Assessment of metagenomic assembly using simulated next generation sequencing data. Best.

I think this might be what you are looking for:

Shakya, Migun, et al. "Comparative metagenomic and rRNA microbial diversity characterization using archaeal and bacterial synthetic communities." Environmental microbiology (2013).

yes

Nat Methods. 2007 Jun;4(6):495-500. Epub 2007 Apr 29.

Use of simulated data sets to evaluate the fidelity of metagenomic processing

methods.

Mavromatis K(1), Ivanova N, Barry K, Shapiro H, Goltsman E, McHardy AC, Rigoutsos

I, Salamov A, Korzeniewski F, Land M, Lapidus A, Grigoriev I, Richardson P,

Hugenholtz P, Kyrpides NC.

...

Comment in

Nat Methods. 2007 Jun;4(6):479-80.

"Metagenomics is a rapidly emerging field of research for studying microbial

communities. To evaluate methods presently used to process metagenomic sequences,

we constructed three simulated data sets of varying complexity by combining

sequencing reads randomly selected from 113 isolate genomes. These data sets were

designed to model real metagenomes in terms of complexity and phylogenetic

composition. We assembled sampled reads using three commonly used genome

assemblers (Phrap, Arachne and JAZZ), and predicted genes using two popular

gene-finding pipelines (fgenesb and CRITICA/GLIMMER). The phylogenetic origins of

the assembled contigs were predicted using one sequence similarity-based (blast

hit distribution) and two sequence composition-based (PhyloPythia,

oligonucleotide frequencies) binning methods. We explored the effects of the

simulated community structure and method combinations on the fidelity of each

processing step by comparison to the corresponding isolate genomes. The simulated

data sets are available online to facilitate standardized benchmarking of tools

for metagenomic analysis."

PMID: 17468765 [PubMed - indexed for MEDLINE]