Getting Started
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Signing up is easy. Provide an email and password - your account is used to store your data and associated experiment notebooks.
You can permanently delete you data at any time.
Alternatively, try the demo account (press "Try Demo" from the ) which includes example datasets from the following studies:
Sze et al. (can also be added in a newly registered account)
Moitinho-Silva et al.
Ravenscraft et al.
If you are following the dada2 tutorial () to create an ASV table, note the following instructions when creating the input to Mian.
Because, Mian will require a CSV or TSV file input, so we need to save some of the objects that dada2 produces. These steps assume you have completed the tutorial up to the "Assign Taxonomy" step:
Save the filtered ASV table:
write.csv(seqtab.nochim, "<some output directory>/seqtab.csv")
Save the taxonomy file:
write.csv(taxa, "<some output directory>/seqtab.csv")
Note that you will still need to create a sample metadata file following the format below.
Mian accepts two commonly-used input formats: BIOM and TSV/CSV files - switch between them using the toggle at the top.
Certain metadata files are common to both formats.
You can either include the sample metadata in the BIOM file or upload it in a separate file.
This file must be one of the following formats. The former is a .shared file produced by mothur, the latter is a manually created OTU/ASV file.
Counts should be integers. Headers are required (OTU/ASV names taken from headers).
Subsampling is optional (further subsampling will be an option in the next step).
This file should contain any categorical or quantitative metadata specific to each sample. TSV or CSV.
The first row is the header. The headers will be converted to filters.
TSV or CSV taxonomy file with each row representing an OTU and its corresponding taxonomy information. Not applicable for BIOM-type uploads. Several taxonomy file contents are accepted:
Example Taxonomy File (GreenGenes or Silva Taxonomy String):
Example Taxonomy File (decomposed taxonomy):
If you have access to gene expression data (eg. your study involves a human subject and you have access to microarray data), optionally include a TSV or CSV gene expression matrix file where the rows are the genes and each column is a sample.
Every sample in the OTU file must be present in this file.
After uploading the files, you'll be directed to page that looks like the following.
The left panel previews the OTU count for each sample after applying the selected normalization - ensure this is what you expect. Here, 67 samples are subsampled to 676.
If auto-subsampling produces a low number, your data might have outliers. Optionally choose to remove these outliers or define your own subsampling threshold.
is a commonly-used biological matrix file format that contains both the OTU/ASV data file and the taxonomy information.
Example :
Newick-formatted phylogenetic tree, where the leaves are the OTUs from the OTU table. This is only needed if you want to use distances in your analysis. Note that not all OTU-picking pipelines will produce a phylogenetic tree.
Subsampling OTU tables is a point of contention in the research community (, ), but is recommended here for comparative analysis. You may choose to proceed without normalization.
