kegg-metabolism [artifact]

The long format output modes produce tab-delimited files. Each line in the file (except for the header line) is indexed by an integer in the unique_id column. Different output “modes” will result in output files with different information.

‘Modules’ Mode

The ‘modules’ output file will have the suffix modules.txt. Each line in the file will represent information about a KEGG module in a given genome, metagenome, or bin. Here is one example, produced by running metabolism estimation on the Infant Gut dataset:

unique_id	db_name	genome_name	kegg_module	module_name	module_class	module_category	module_subcategory	module_definition	kofam_hits_in_module	gene_caller_ids_in_module	module_completeness	module_is_complete
0	E_faecalis_6240	Enterococcus_faecalis_6240	M00001	Glycolysis (Embden-Meyerhof pathway), glucose => pyruvate	Pathway modules	Carbohydrate metabolism	Central carbohydrate metabolism	””“(K00844,K12407,K00845,K00886,K08074,K00918) (K01810,K06859,K13810,K15916) (K00850,K16370,K21071,K00918) (K01623,K01624,K11645,K16305,K16306) K01803 ((K00134,K00150) K00927,K11389) (K01834,K15633,K15634,K15635) K01689 (K00873,K12406)”””	K01834,K00134,K00873,K01689,K01624,K01803,K00927,K00850,K01810,K00845	2342,2646,1044,642,226,1041,348,1042,1043,225,600,1608	1.0	True
1	E_faecalis_6240	Enterococcus_faecalis_6240	M00002	Glycolysis, core module involving three-carbon compounds	Pathway modules	Carbohydrate metabolism	Central carbohydrate metabolism	”"”K01803 ((K00134,K00150) K00927,K11389) (K01834,K15633,K15634,K15635) K01689 (K00873,K12406)”””	K01834,K00134,K00873,K01689,K01803,K00927	2342,2646,1044,642,226,1041,1042,1043	1.0	True
(…)	(…)	(…)	(…)	(…)	(…)	(…)	(…)	(…)	(…)	(…)	(…)	(…)

‘KOfam Hits in Modules’ Mode

The ‘kofam_hits_in_modules’ output file will have the suffix kofam_hits_in_modules.txt. Each line in the file will represent information about one KOfam hit in a given genome, metagenome, or bin - but ONLY KOs that are a part of at least one KEGG Module are included in this output. Hits are organized according to the KEGG module that they belong to, and more specifically the path through the KEGG module in which the KO appears.

What is a path through a KEGG module, you ask? Well. KEGG modules are metabolic pathways defined by a set of KOs. For example, here is the definition of module M00001, better known as “Glycolysis (Embden-Meyerhof pathway), glucose => pyruvate”:

(K00844,K12407,K00845,K00886,K08074,K00918) (K01810,K06859,K13810,K15916) (K00850,K16370,K21071,K00918) (K01623,K01624,K11645,K16305,K16306) K01803 ((K00134,K00150) K00927,K11389) (K01834,K15633,K15634,K15635) K01689 (K00873,K12406)

Spaces separate steps (reactions) in the metabolic pathway, and commas separate alternative KOs or alternative sub-pathways that can facilitate the same overall reaction. So a definition such as the one above can be “unrolled” into several different linear sequences of KOs, each of which we consider to be a possible “path” through the module. As an example, we can take the first option for every step in the Embden-Meyerhof pathway definition from above:

(K00844,K12407,K00845,K00886,K08074,K00918) (K01810,K06859,K13810,K15916) (K00850,K16370,K21071,K00918) (K01623,K01624,K11645,K16305,K16306) K01803 ((K00134,K00150) K00927,K11389) (K01834,K15633,K15634,K15635) K01689 (K00873,K12406)

to get the following path of KOs (which happens to be the path shown in the output example below):

K00844 K01810 K00850 K01623 K01803 K00134 K00927 K01834 K01689 K00873

For every KO in the path above that has a hit in the contigs-db, there will be a corresponding line in the ‘kofam_hits’ output file. The same will occur for every possible path in every single KEGG module, resulting in a lot of lines and extremely repetitive but nicely parseable information.

Without further ado, here is an example of this output mode (also from the Infant Gut dataset):

unique_id	db_name	kofam_hit	gene_caller_id	contig	path_id	path	path_completeness	genome_name	kegg_module	module_completeness	module_is_complete
0	E_faecalis_6240	K01834	2342	Enterococcus_faecalis_6240_contig_00003_chromosome	0	K00844,K01810,K00850,K01623,K01803,K00134,K00927,K01834,K01689,K00873	0.8	Enterococcus_faecalis_6240	M00001	1.0	True
1	E_faecalis_6240	K01834	2646	Enterococcus_faecalis_6240_contig_00003_chromosome	0	K00844,K01810,K00850,K01623,K01803,K00134,K00927,K01834,K01689,K00873	0.8	Enterococcus_faecalis_6240	M00001	1.0	True
(…)	(…)	(…)	(…)	(…)	(…)	(…)	(…)	(…)	(…)	(…)	(…)

‘KOfam Hits’ Mode

The kofam_hits output file will have the suffix kofam_hits.txt. Unlike the previous mode, this output will include ALL KOs, regardless of whether they belong to a KEGG Module or not. However, since only a subset of these KOs belong to modules, this output does not include module-related information like paths and module completeness.

Here is an example of this output mode (also from the Infant Gut dataset):

unique_id	db_name	genome_name	ko	gene_caller_id	contig	modules_with_ko	definition
0	E_faecalis_6240	Enterococcus_faecalis_6240	K00845	1608	Enterococcus_faecalis_6240_contig_00003_chromosome	M00001,M00549,M00892,M00909	glucokinase [EC:2.7.1.2]
1	E_faecalis_6240	Enterococcus_faecalis_6240	K01810	600	Enterococcus_faecalis_6240_contig_00003_chromosome	M00001,M00004,M00114,M00892,M00909	glucose-6-phosphate isomerase [EC:5.3.1.9]
2	E_faecalis_6240	Enterococcus_faecalis_6240	K00850	225	Enterococcus_faecalis_6240_contig_00003_chromosome	M00001,M00345	6-phosphofructokinase 1 [EC:2.7.1.11]
(…)	(…)	(…)	(…)	(…)	(…)	(…)	(…)

Custom Mode (for module data)

The ‘modules_custom’ output mode will have user-defined content and the suffix modules_custom.txt (we currently only support output customization for modules data). See anvi-estimate-metabolism for an example command to work with this mode.

Matrix format output

Matrix format is an output option when anvi-estimate-metabolism is working with multiple contigs databases at once. The purpose of this output mode is to generate matrices of KEGG module statistics for easy visualization. Currently, the output of this mode includes a module completeness matrix, a matrix of binary module presence/absence values, and a matrix of KO counts. In these matrices, each row is a KEGG module or KO, and each column is an input contigs-db.

Here is an example of a module completeness matrix:

module	bin_1	bin_2	bin_3	bin_4	bin_5	bin_6
M00001	1.00	0.00	1.00	1.00	1.00	0.00
M00002	1.00	0.00	1.00	1.00	1.00	1.00
M00003	0.88	0.00	1.00	0.75	1.00	0.88
M00004	0.88	0.00	0.88	0.88	0.88	0.00
M00005	1.00	0.00	1.00	1.00	1.00	1.00
(…)	(…)	(…)	(…)	(…)	(…)	(…)

While the above is the default matrix format, some users may want to include more annotation information in the matrices so that it is easier to know what is going on when looking at the matrix data manually. You can add this metadata to the matrices by using the --include-metadata flag when running anvi-estimate-metabolism, and the output will look something like the following:

module	module_name	module_class	module_category	module_subcategory	bin_1	bin_2	bin_3	bin_4	bin_5	bin_6
M00001	Glycolysis (Embden-Meyerhof pathway), glucose => pyruvate	Pathway modules	Carbohydrate metabolism	Central carbohydrate metabolism	1.00	0.00	1.00	1.00	1.00	0.00
M00002	Glycolysis, core module involving three-carbon compounds	Pathway modules	Carbohydrate metabolism	Central carbohydrate metabolism	1.00	0.00	1.00	1.00	1.00	1.00
M00003	Gluconeogenesis, oxaloacetate => fructose-6P	Pathway modules	Carbohydrate metabolism	Central carbohydrate metabolism	0.88	0.00	1.00	0.75	1.00	0.88
(…)	(…)	(…)	(…)	(…)	(…)	(…)

Edit this file to update this information.