MetaQuery: quantitative analysis of the human gut microbiome

Frequently Asked Questions


Q: How can I query the abundance of a specific organism, rather than a specific gene?

A: First, try searching for this organism by name. You can also seach MetaQuery by sequence. Try using a phylogenetic marker gene (e.g. 16S) with a strict identity cutoff (e.g. 98%) or use a gene that is specific to your organism.


Q: What are the best alignment parameters to use?

A: This depends on whether you are interested in close or remote homologs of your query. For close homologs, use high percent identity cutoffs (e.g. 90, 95, 98%) and/or low E-value cutoffs. For remote homologs, use a lower percent identity cutoff and/or higher E-value cutoff. The default values may be too lenient for your application. You can also run MetaQuery using several cutoffs and compare your results.


Q: What does "average copy number" mean, and how does MetaQuery estimate this?

A: This is an abundance metric for a gene or gene family. It indicates the average number of gene copies per cell in a microbial community. It is obtained by normalizing gene abundances by the abundance of a group of universal single copy genes. So, a value of 1.0 indicates that a gene is present once per cell on average; a value of 0.01 as present once per 100 cells on average.


Q: Why didn't I receive an email notifying me that my job was complete?

A: First, check your spam folder. Second, make sure you entered the correct email and the name that corresponds to your email address. You can also the check the status of your job on the Jobs page.


Q: How do I cite MetaQuery?

A: If you use MetaQuery, please use the following citation:
Nayfach S, Fischbach MA, Pollard KS. MetaQuery: a web server for rapid annotation and quantitative analysis of specific genes in the human gut microbiome. Bioinformatics 2015;31(14). doi:10.1093/bioinformatics/btv382
Also, be sure to cite the various resources, studies, and tools utilized by MetaQuery. These references can be found on the About page.