{"id":21280623,"url":"https://github.com/borgwardtlab/hogimine","last_synced_at":"2025-10-24T08:25:19.690Z","repository":{"id":69455224,"uuid":"591231639","full_name":"BorgwardtLab/HOGImine","owner":"BorgwardtLab","description":"Higher-order genetic interaction discovery with network-based biological priors.","archived":false,"fork":false,"pushed_at":"2024-02-08T16:59:55.000Z","size":52257,"stargazers_count":5,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-02-08T17:57:37.445Z","etag":null,"topics":["bioinformatics","gwas-tools","ismb2023","pattern-mining"],"latest_commit_sha":null,"homepage":"","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/BorgwardtLab.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2023-01-20T08:42:28.000Z","updated_at":"2024-02-02T18:23:04.000Z","dependencies_parsed_at":"2024-02-08T17:54:45.210Z","dependency_job_id":null,"html_url":"https://github.com/BorgwardtLab/HOGImine","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2FHOGImine","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2FHOGImine/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2FHOGImine/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2FHOGImine/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/BorgwardtLab","download_url":"https://codeload.github.com/BorgwardtLab/HOGImine/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":225715515,"owners_count":17512903,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bioinformatics","gwas-tools","ismb2023","pattern-mining"],"created_at":"2024-11-21T10:37:23.118Z","updated_at":"2025-10-24T08:25:19.628Z","avatar_url":"https://github.com/BorgwardtLab.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"# HOGImine\nHOGImine (Higher-Order Genetic Interaction miner), is a pattern-mining-based algorithm for finding genetic meta-markers, i.e. combinations of genetic markers, that show a statistical association with a phenotype.\nCompared to the state-of-the-art miners, it expands the class of discoverable genetic meta-markers \nby considering higher-order interactions of genes and by allowing multiple encodings for the\ngenetic variants. Moreover, our method can exploit prior biological knowledge on\ngene interactions, such as protein-protein interaction networks, genetic pathways and protein complexes,\nto restrict its search space. HOGImine accepts both binary encodings and additive encodings for the markers.\n\n| ![](HogiMine.png) |\n|:--| \n| *Examples of meta-markers considered by HOGImine. **(a)** The dataset features, for each sample, a vector of genetic markers with additive encoding. The markers are subdivided into genes, in the figure highlighted by pale colors. **(b)** Information on the interactions among genes if usually provided via a PPI network. **(c)** The black solid meta-marker (shown in Panel a) spans three genomic intervals in the violet, yellow and azure genes, which form a connected subgraph in the network, using the dominant encoding for all three. **(d)** The black dashed meta-marker spans three genomic intervals in the yellow, green and red genes, which form a connected subgraph in the network, using the recessive encoding for all three.*|\n\n### Citing our work \nHOGImine is described in the following paper:\n\u003e Paolo Pellizzoni, Giulia Muzio and Karsten Borgwardt. *Higher-order genetic interaction discovery with network-based biological priors.* ISMB 2023. [[PDF online]](https://academic.oup.com/bioinformatics/article/39/Supplement_1/i523/7210485?login=false) \n\n\n### Compilation\nCompilation uses make. Currently the code is compiled with ```gcc-12```, but other compilers might work as well.\n```\ncd src\nmake\n```\n\nTo decompress the SNP data in the *data/mmusculus* folder, use the following command. \n```\nunzip data/mmusculus/BMC.Mode/BMC.Mode_X_T.txt.zip -d data/mmusculus/BMC.Mode/\n```\n\n### Options\nThe options for HOGImine are:\n- ```-i file```: marker (binary or additive encoding) file. It should be matrix of size $n. SNPs \\times n. samples$, i.e. with each column being a sample.\n- ```-l file```: labels file. It should be a binary matrix of size $n. samples \\times 1$.\n- ```-s file```: SNP names file. It should be a file with $n. SNPs$ rows, containing the names of the SNPs.\n- ```-c file```: covariate file. It should be a matrix of size $n. samples \\times 1$ taking values in $\\{ 1, \\dots, C \\}$, with $C$ being the number of covariate classes.\n- ```-m file```: SNP map file. It should be a file with $n. genes$ rows. The first entry of each row should be the the gene name, and the following entries should be the SNPs that are mapped to that gene.\n- ```-e file```: gene interactions file. It should be a file with $n. interactions$ rows. Each row should contain a set of genes that are known to be interacting (biological priors).\n- ```-f level```: target fwer (e.g. 0.05).\n- ```-o or -O file```: output file name, with -o in compressed format and with -O in verbose format.\n- ```-p p```: number $p$ of permutations (default $0$), if $p \u003e 0$ it runs a permutation testing procedure.\n- ```-d d```: maximum SNP interval length in each gene.\n- ```-v```: outputs all the testable patterns.\n\n\n\n### Usage example (binary data)\n```\n./src/hogimine_additive -i data/athaliana/interactome_0kb/avrRpm1/avrRpm1_X.txt -l data/athaliana/interactome_0kb/avrRpm1/avrRpm1_Y.txt -c data/athaliana/covar_snps/avrRpm1/avrRpm1_covar_n2.txt -s data/athaliana/interactome_0kb/avrRpm1/avrRpm1_snpID.txt -m data/athaliana/interactome_0kb/avrRpm1/avrRpm1_snp_map.txt -e data/athaliana/athal_ppi/genes+edges+3cliques+complexes.txt -f 0.05 -O out_athaliana\n```\nOutput: each pattern is reported on a row, the first column reports the CMH p-value of the pattern, then the interacting genes spanned by the pattern are reported, and finally the SNP positions composing the pattern.\n```\n3.27815e-12; AT3G07040, AT3G25070; Chr3_2227817, Chr3_9133148\n1.33438e-11; AT3G07040; Chr3_2227817\n2.22304e-11; AT3G07040, AT3G25070; Chr3_2227817, Chr3_9132644\n2.22304e-11; AT3G07040, AT5G51450; Chr3_2227817, Chr5_20897395\n...\n```\n\n### Usage example (additive data)\n```\n./src/hogimine_additive -i data/mmusculus/BMC.Mode/BMC.Mode_X_T.txt -l data/mmusculus/BMC.Mode/BMC.Mode_y_bin.txt -c data/mmusculus/BMC.Mode/BMC.Mode_kinship.txt -s data/mmusculus/BMC.Mode/SNPs_ids.txt -m data/mmusculus/BMC.Mode/gene2snps.txt -e data/mmusculus/BMC.Mode/all_int_compl.txt -f 0.05 -O out_mus\n```\n\nOutput: each pattern is reported on a row, the first column reports the CMH p-value of the pattern, then the interacting genes spanned by the pattern are reported along with the encoding for the SNPs, and finally the SNP positions composing the pattern.\n\n```\n3.65197e-25; ENSMUSG00000047040 (dominant), ENSMUSG00000048175 (recessive); chr11_96928685, chr15_98155192\n3.65197e-25; ENSMUSG00000047040 (dominant), ENSMUSG00000048175 (recessive); chr11_96930807, chr15_98157791\n...\n4.58913e-25; ENSMUSG00000061298 (dominant), ENSMUSG00000038756 (dominant); chr4_110873242, chr11_96148817\n...\n1.76405e-24; ENSMUSG00000057058 (dominant), ENSMUSG00000022148 (recessive); chr11_96573406, chr11_96584561, chr15_6571463\n1.8372e-24; ENSMUSG00000018672 (dominant), ENSMUSG00000060992 (recessive); chr11_96859685, chr15_103292285\n...\n```\n\n### Acknowledgements\nThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 813533 (K.B.).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fborgwardtlab%2Fhogimine","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fborgwardtlab%2Fhogimine","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fborgwardtlab%2Fhogimine/lists"}