Commit 336f9827 authored by Bastien Macé's avatar Bastien Macé
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swarm step

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### IV - 3 - SWARM processing step (Pipelines C)
In pipelines C, SWARM gathers the sequences in OTU thanks to this algorithm :
- First, sequences are pairwise aligned to count the number of dissimilarities between them
- A threshold _d_ is chosen, when the number of dissimilarities is inferior or equal to _d_, both sequences are gathered in a same OTU
- This process is repeated to add iteratively the sequences to an OTU
- The most abundant sequence of each OTU is chosen to represent the OTU
- The abundance of the OTU is constituted by adding the abundances of each sequence included in the OTU
The following line process the algorithm :
```
swarm -z -d 1 -o stats_Aquarium_2.txt -w Aquarium_2.clustered.fasta < Aquarium_2.fasta
# "-z" option permits to accept the abundance in the header, provided that there is no space in the header and that the value is preceded by "size="
# "-d" is the maximal number of differences tolerated between 2 sequences to be gathered in the same OTU (1 here)
# "-o" option returns a ".txt" file in which each line corresponds to an OTU with all the amplicons belonging to this OTU
# "-w" option gives a "fasta" file with the representative sequence of each OTU
```
An option called _fastidious_ can be added, with _-f_, in order to integrate small OTUs in larger related OTUs. We don't use it here because it doesn't change the output at all in our study.
For more details on this SWARM processing step, see the original publication [here](https://doi.org/10.1038/nmeth.3869).
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### IV - 4 - SWARM + LULU processing step (Pipelines D)
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### IV - 4 - SWARM + LULU processing step (Pipelines D)
For more details on LULU, see the original publication [here](https://doi.org/10.1038/nmeth.3869).
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