Here we quickly shows the use of Hoea without installation

1, ho = what?
Gene ontology and KEGG orthology are hierarchical structured, so the 'ho' here represnts the hierarchical ontology. One ho have a definition, and have many relationships with other ho.

2, Get Hoea tarbar source from Download. Decompress it. Change to the new created Hoea-[version] directory. ( $ as the shell command prompt, same as below).

$ wget http://sourceforge.net/projects/hoea/files/0.1.2/Hoea-[version].tar.gz/download
$ tar zxvf Hoea-[version].tar.gz
$ cd Hoea-[version]

3, There is some executable files of this module, and we have also prepared some sample data for illustration. So change to the src/Hoea/sample directory.

$ cd src/Hoea/sample/

4, For an Hoea analysis, you actually need 2 files. The sample data were taken from BMC Genomics. 2009 Nov 11;10(1):517, which contains microarray data of model legume Medicago truncatula under salt stress. Input for Hoea are the two files in sample directory, mt_probe_go.txt and probe_6h_up.txt.
mt_probe_go.txt file contains Gene ontology annotation of probe sets of Medicago truncatula microarry, part of the files looks like:

Mtr.32952.1.S1_s_at     GO:0016301
Mtr.32952.1.S1_s_at     GO:0006014
Mtr.32952.1.S1_s_at     GO:0009507
Mtr.51583.1.S1_at       GO:0008270
Mtr.51583.1.S1_at       GO:0003676
Mtr.51583.1.S1_at       GO:0005622
Mtr.6693.1.S1_s_at      GO:0009658
Mtr.6693.1.S1_s_at      GO:0005198
Mtr.6693.1.S1_s_at      GO:0016226
Mtr.6693.1.S1_s_at      GO:0009507
this is a two column file, the first column is the probe set, the second is the GO terms which annotated to the correspond probe set.
the probe_6h_up.txt file contails probe sets selected from up-regulated probe sets at time point 6 hour, it is looks like:
this file contains one probe set per line.

5, after we prepare those 3 things we need, we could start the Hoea run, notice that we located at the sample directory right now. just run the following command:

 $ python ../Hoea.py -a mt_probe_go.txt -i probe_6h_up.txt
some information will print to the screen:
read in ho relationship file... done
read in ho definition file... done
read in background ho annotations... done
generate ho term to gene id mapping,this may take a little while...
start analysis...
input 520 items for analysis, 366 items with annotations
18248 items have annotations in background
All Done!
also, some additional file were generated in current directory. the name of these files all start with the input analysis file probe_6h_up.txt, files contains now include:
mt_probe_go.txt           probe_6h_up.txt_GO_1.png  probe_6h_up.txt_GO_3.dot  probe_6h_up.txt_Rcom.Rout
probe_6h_up.txt           probe_6h_up.txt_GO_2.dot  probe_6h_up.txt_GO_3.pdf  probe_6h_up.txt_Rinput.txt
probe_6h_up.txt_GO_1.dot  probe_6h_up.txt_GO_2.pdf  probe_6h_up.txt_GO_3.png  probe_6h_up.txt_Routput.txt
probe_6h_up.txt_GO_1.pdf  probe_6h_up.txt_GO_2.png  probe_6h_up.txt_Rcom.R

5, explanation of the command. in last step, we run the command python ../Hoea.py -a mt_probe_go.txt -i probe_6h_up.txt -t 50900 to finish the analysis. when -a option specifies the annotation file, -i option specifies the input file for analysis, the -t option specifies the total number. the script Hoea.py support many other options like:

$ python ../Hoea.py -h
Usage: Hoea.py -i input file -r ho.relation -d ho.definition -a annotation_file -s output_prefix -p pvalue_cutoff -n number_cutoff

  --version             show program's version number and exit
  -h, --help            show this help message and exit
  -i INPUT, --input=INPUT
                        input file for analysis
  -r HOREL, --ho-relation=HOREL
                        ho relation file
  -d HODEF, --ho-definition=HODEF
                        ho definition file
  -a ANNOTATION, --annotation=ANNOTATION
                        annotation file
  -p PVALUE, --pvalue=PVALUE
                        FDR adjust P-value cutoff of ho terms [default: 0.05]
  -n NUMBER, --number=NUMBER
                        number cutoff of an ho term with iterm assigned
                        [default: 5]
  -s PREFIX, --prefix=PREFIX
                        prefix of output file [default: input filename]

6, explanation of the output. the final analysis result was stored in the file probe_6h_up.txt_Routput.txt, this is a tab-delimited file. One line of this file looks like:

GO:0022622      root system development 3       520     0.0032416502947 165     Mtr.12392.1.S1_at//Mtr.15877.1.S1_at//Mtr..12155.1.S1_at 0.238860994920602       1
every row of this file starts with a ho term, like GO:0022622, the following fields are the description of this term, probe sets assigned to this terms in input file, total number of probe sets in input file, annotation rate of this term (165/50900), probe sets assigned to this terms in the annotation file, '//' seperated probe sets belong to this term, p-value, FDR-adjust p-value (Q-value), respectively.
also, some graphs were generated during the analysis, the probe_6h_up.txt_GO_1.png illustrated the enrichment situation of probe sets belong to the biological_process term: GO:0008150
part of this graph:

the fill color of each box means the statistical significant level, explained below:

the relationship between each term were connected by lines with different color, blue means 'is_a', purple means 'regulates',
the color used was determinted by GO.relations from the Gene Ontology website.
other files like *.R file are the R scripts used for statistical calculation, the *.dot file are used by Graphviz for drawing those graphs.

7, update the ho relationship files and definition files
change to the data directory of Hoea module:

$ cd ../data/
the files contains in the directory are:
go.def  go.rel  ko.def  ko.rel
the .def file means ho definition file and .rel file means ho relationship file.
as the Gene ontology and KEGG organization update their files frequently, Hoea contains two scripts GOIterator.py and KOIterator.py to help generating newest definition and relationship file.

$ python GOIterator.py -h
Usage: GOIterator.py -g gene_ontology_ext.obo -r go.relation -d go.definition

  --version             show program's version number and exit
  -h, --help            show this help message and exit
  -g GOFILE, --go-file=GOFILE
                        specify the GO file
  -r OUTREL, --output-relation=OUTREL
                        output GO relation file
  -d OUTDEF, --output-difinition=OUTDEF
                        output GO definition file
the newest gene_ontology_ext.obo file is always available at: ftp://ftp.geneontology.org/go/ontology/obo_format_1_2/gene_ontology_ext.obo
$ python KOIterator.py -h
Usage: KOIterator.py -k ko -r ko.relation -d ko.definition

  --version             show program's version number and exit
  -h, --help            show this help message and exit
  -k KOFILE, --ko-file=KOFILE
                        specify the KO file
  -r OUTREL, --output-relation=OUTREL
                        output KO relation file
  -d OUTDEF, --output-difinition=OUTDEF
                        output KO definition file
the newest ko file is always available at: ftp://ftp.genome.jp/pub/kegg/genes/ko

Next,we will show a KEGG orthology enrichment analysis example

this sample data were taken from a de novo transcriptome sequencing project of Medicago falcata (unpublished). the first 10 lines of annotation files looks like:

1_scaffold_10016-1      K12867
1_scaffold_19693-0      K08803
1_scaffold_4523-0       K02149
1_scaffold_25008-0      K10257
1_scaffold_22510-0      K04077
1_scaffold_17237-0      K03063
1_scaffold_5829-1       K11975
1_scaffold_13429-0      K10712
1_scaffold_4963-0       K01714
1_scaffold_20563-0      K13468
this file is also a two column file, the first column indicate the transcripts id (from de novo assembly), the second column is the KO annotation terms. let's select some transcripts for enrichment analysis using Hoea.
the command line are as follows, you might noticed that we specified the -n and -p option, which means the number cutoff of transcripts assigned to a KO term and the corresponding FDR-adjust p value cutoff, respectively. the -s option specifies the prefix of the output result files.
 $ python Hoea-version/src/Hoea/Hoea.py -i com5up.txt -a all.ko -s wahaha -n 0 -p 0.5
also some information will print to the screen:
read in ho relationship file... done
read in ho definition file... done
read in background ho annotations... done
generate ho term to gene id mapping,this may take a little while...
start analysis...
input 336 items for analysis, 158 items with annotations
55195 items have annotations in background
All Done!
file generated are listed below:
wahaha_KO_1.dot  wahaha_KO_2.pdf  wahaha_KO_3.png  wahaha_KO_5.dot  wahaha_KO_6.pdf   wahaha_Rinput.txt
wahaha_KO_1.pdf  wahaha_KO_2.png  wahaha_KO_4.dot  wahaha_KO_5.pdf  wahaha_KO_6.png   wahaha_Routput.txt
wahaha_KO_1.png  wahaha_KO_3.dot  wahaha_KO_4.pdf  wahaha_KO_5.png  wahaha_Rcom.R
wahaha_KO_2.dot  wahaha_KO_3.pdf  wahaha_KO_4.png  wahaha_KO_6.dot  wahaha_Rcom.Rout
as the first class of KO hierarchical structural contaons 6 terms, this will generate 6 graphs.
as the relationships between KO terms are not specified as GO like,so the terms were all connected with blue lines (which mean 'is_a' in GO).