16S rRNA sequencing tells you which bacteria are in a sample. The usual route involves several tools, reference databases and a lot of setup. This guide shows how the same analysis runs inside Omicsboard Lab, on your own machine, with Omi explaining each step.
What you need
- A 16S FASTQ file, single-end, paired-end or interleaved.
- Omicsboard Lab installed, with the local environment set up.
Step 1: attach the file and describe your goal
Attach the FASTQ and tell Omi what you want, for example "profile the bacterial community in this sample". Your reads stay on your computer. Omi works with the file where it is.
Step 2: check the sample first
Omi starts by inspecting the data: read count, read lengths, whether the file is paired or interleaved, and a quality plot. It also looks for common 16S primers, so you know which region was sequenced. If something looks wrong, this is where you find out.
Step 3: approve the plan
Omi writes out a numbered plan and waits for your go-ahead. This is your chance to change direction, for example to choose a different reference database.
Step 4: classify the reads
Omi classifies every read against a real reference database. For a complete analysis it uses SILVA, which carries full lineage and handles archaea and organelle sequences well. For a quick bacterial snapshot, NCBI 16S is faster. In our tests on a sample of roughly 150,000 reads, NCBI 16S took about a minute and SILVA a few minutes.
Step 5: read the results
You get a genus-level community profile saved as a table, plus diversity measures (richness, Shannon, Simpson, evenness), a rank-abundance curve, composition by phylum and an interactive sunburst chart you can click through. Omi then builds a phylogenetic tree of the most abundant genera and explains what the community suggests biologically.
An honest limit: this k-mer approach is reliable to genus level. It cannot separate closely related species, because their 16S sequences are almost identical. For exact species-level variants, Omi points you to a denoising workflow (DADA2) on Galaxy rather than guessing.
Step 6: choose what to do next
Omi finishes with a list of follow-ups: compare samples, test for differences between groups, look at the core and rare members of the community, or turn the analysis into a written report you can export.
Tips
- Say up front if you have several samples, so Omi can plan comparisons.
- If a result surprises you, ask why. Omi shows the method and its caveats, not just the picture.
- Save the notebook when you finish. It contains the code and outputs, so you can rerun the analysis later.