filter_otus_from_otu_table.py – Filter OTUs from an OTU table based on their observation counts or identifier.

Description:

Usage: filter_otus_from_otu_table.py [options]

Input Arguments:

Note

[REQUIRED]

-i, --input_fp

The input otu table filepath in biom format

-o, --output_fp

The output filepath in biom format

[OPTIONAL]

--negate_ids_to_exclude

Keep OTUs in otu_ids_to_exclude_fp rather than discard them [default:False]

-n, --min_count

The minimum total observation count of an otu for that otu to be retained [default: 0]

--min_count_fraction

Fraction of the total observation (sequence) count to apply as the minimum total observation count of an otu for that otu to be retained. this is a fraction, not percent, so if you want to filter to 1%, you specify 0.01. [default: 0]

-x, --max_count

The maximum total observation count of an otu for that otu to be retained [default: infinity]

-s, --min_samples

The minimum number of samples an OTU must be observed in for that otu to be retained [default: 0]

-y, --max_samples

The maximum number of samples an OTU must be observed in for that otu to be retained [default: infinity]

-e, --otu_ids_to_exclude_fp

File containing list of OTU ids to exclude: can be a text file with one id per line, a text file where id is the first value in a tab-separated line, or can be a fasta file (extension must be .fna or .fasta) [default: None]

Output:

Singleton filtering:

Discard all OTUs that are observed fewer than 2 times (i.e., singletons)

filter_otus_from_otu_table.py -i otu_table.biom -o otu_table_no_singletons.biom -n 2

Abundance filtering:

Discard all OTUs that are observed greater than 100 times (e.g., if you want to look at low abundance OTUs only)

filter_otus_from_otu_table.py -i otu_table.biom -o otu_table_low_abundance.biom -x 100

Chimera filtering:

Discard all OTUs listed in chimeric_otus.txt (e.g., to remove chimeric OTUs from an OTU table)

filter_otus_from_otu_table.py -i otu_table.biom -o otu_table_non_chimeric.biom -e chimeric_otus.txt