[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-google-deepmind-ucsc-conservation-and-tfbs":3,"mdc-nsayrw-key":33,"related-repo-google-deepmind-ucsc-conservation-and-tfbs":1402,"related-org-google-deepmind-ucsc-conservation-and-tfbs":1509},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":22,"repoUrl":23,"updatedAt":24,"license":25,"forks":26,"topics":27,"repo":28,"sourceUrl":31,"mdContent":32},"ucsc-conservation-and-tfbs","fetch genomic conservation and binding data","Fetch Evolutionary Conservation scores (phyloP, phastCons) and Transcription Factor Binding Sites (TFBS) from the UCSC Genome Browser. Use when analyzing whether genomic variants or regions are evolutionarily conserved, functionally important, or bounded by TF regulators across major projects (ENCODE, JASPAR, ReMap).\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"google-deepmind","Google DeepMind","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fgoogle-deepmind.png",[12,16,19],{"name":13,"slug":14,"type":15},"Research","research","tag",{"name":17,"slug":18,"type":15},"Life Sciences","life-sciences",{"name":20,"slug":21,"type":15},"Genetics","genetics",2333,"https:\u002F\u002Fgithub.com\u002Fgoogle-deepmind\u002Fscience-skills","2026-07-12T07:52:16.138982",null,234,[],{"repoUrl":23,"stars":22,"forks":26,"topics":29,"description":30},[],"GDM Science Skills to speed up agentic scientific workflows with better grounding and higher token efficiency. Integrate insights from AlphaGenome, AFDB, UniProt and 30+ other databases and tools.","https:\u002F\u002Fgithub.com\u002Fgoogle-deepmind\u002Fscience-skills\u002Ftree\u002FHEAD\u002Fskills\u002Fucsc_conservation_and_tfbs","---\nname: ucsc-conservation-and-tfbs\ndescription: >\n  Fetch Evolutionary Conservation scores (phyloP, phastCons) and Transcription\n  Factor Binding Sites (TFBS) from the UCSC Genome Browser. Use when analyzing\n  whether genomic variants or regions are evolutionarily conserved, functionally\n  important, or bounded by TF regulators across major projects (ENCODE, JASPAR,\n  ReMap).\n---\n\n# Conservation Scores & TFBS Lookup (UCSC)\n\nThis skill provides access to evolutionary constraint scores and conserved\nelements from the UCSC Genome Browser. It retrieves scores from the PHAST\npackage — specifically `phastCons` (identifying functional blocks) and `phyloP`\n(measuring individual site constraint) — calculated from multiple alignments.\n\nUse this skill to determine if a non-coding variant hits a site that hasn't\nchanged since a common ancestor (which is a strong signal for pathogenicity) or\nto find conservation peaks across a regulatory element.\n\n## Prerequisites\n\n1.  **`uv`**: Read the `uv` skill and follow its Setup instructions to ensure\n    `uv` is installed and on PATH.\n2.  **User Notification**: If .licenses\u002Fucsc_conservation_and_tfbs_LICENSE.txt\n    does not already exist in the workspace root directory then (1) prominently\n    notify the user to check the terms at\n    https:\u002F\u002Fgenome.ucsc.edu\u002Fconditions.html and\n    https:\u002F\u002Fgenome.ucsc.edu\u002FgoldenPath\u002Fhelp\u002Fapi.html, then (2) create the file\n    recording the notification text and timestamp.\n\n## Core Rules\n\n-   **Use the Wrapper**: ALWAYS execute the provided helper scripts to query the\n    database rather than accessing the database directly. The scripts\n    automatically enforce the required rate limit gracefully.\n-   **Large Output Handling**: Always pass --output to redirect output to a\n    file. Parse it separately (using jq or your own code).\n-   **Notification**: If this skill is used, ensure this is mentioned in the\n    output.\n\n## Utility Scripts\n\nThis skill includes scripts to query different types of genomic data from UCSC:\n\n1.  **`scripts\u002Fget_conservation.py`**: For Evolutionary Conservation scores\n    (phyloP, phastCons).\n2.  **`scripts\u002Fget_tfbs.py`**: For Transcription Factor Binding Sites (TFBS).\n3.  **`scripts\u002Flist_tracks.py`**: For listing available tracks based on search\n    or group constraints.\n\nAlways use the `hg38` genome assembly by default, unless the user has specified\notherwise.\n\n### Fetching Conservation for Specific Variants\n\nTo get the evolutionary constraint at a single base, or a list of specific\nbases. This is optimal for single nucleotide variants (SNVs). `phyloP` is the\nbest metric for individual bases.\n\n```bash\nuv run scripts\u002Fget_conservation.py --coordinates \"chr1:215867804\" \"chr1:215867823\" --output \u002Ftmp\u002Fcons_output.json\n```\n\n### Fetching Regions and Conserved Elements\n\nTo identify \"conservation peaks\" across a non-coding regulatory element (like an\nenhancer) to see if an ISM-predicted importance peak aligns with evolutionary\nhistory. `phastCons` is best for functional windows due to HMM smoothing. The\n`--conserved-elements` flag will also retrieve predefined blocks under extreme\nconstraint.\n\n```bash\nuv run scripts\u002Fget_conservation.py --coordinates \"chr8:11748914-11749085\" --conserved-elements --output \u002Ftmp\u002Fregion_cons.json\n```\n\n### Lineage-Specific Constraints\n\nYou can control the evolutionary depth using the `--collection` flag. The\ndefault (`vertebrate`) uses the **100-vertebrate Multiz alignment** for both\nhg38 and hg19, matching the UCSC Genome Browser's default comparative genomics\ntracks.\n\n#### hg38 Collections\n\n-   **`vertebrate`** (default): UCSC 100-vertebrate Multiz alignment. phyloP:\n    `phyloP100way`, phastCons: `phastCons100way`.\n-   **`mammal`**: Hiller Lab 470-way mammalian alignment. phyloP:\n    `phyloP470wayBW`, phastCons: `phastCons470way`.\n-   **`primate`**: UCSC 30-primate Multiz alignment. phyloP: `phyloP30way`,\n    phastCons: `phastCons30way`.\n\n#### hg19 Collections\n\n-   **`vertebrate`** (default): UCSC 100-vertebrate Multiz alignment. phyloP:\n    `phyloP100way`, phastCons: `phastCons100way`.\n-   **`vertebrate46`**: UCSC 46-vertebrate Multiz alignment (legacy). phyloP:\n    `phyloP46wayAll`, phastCons: `phastCons46way`.\n-   **`mammal`**: 46-way placental mammal subset. phyloP:\n    `phyloP46wayPlacental`, phastCons: `phastCons46wayPlacental`.\n-   **`primate`**: 46-way primate subset. phyloP: `phyloP46wayPrimates`,\n    phastCons: `phastCons46wayPrimates`.\n\n```bash\n# hg38 mammal (Hiller 470-way)\nuv run scripts\u002Fget_conservation.py --coordinates \"chr5:1045330-1046172\" --collection mammal --output \u002Ftmp\u002Fmammal_cons.json\n\n# hg19 with legacy 46-vertebrate alignment\nuv run scripts\u002Fget_conservation.py --coordinates \"chr5:1045330-1046172\" --genome hg19 --collection vertebrate46 --output \u002Ftmp\u002Fvert46_cons.json\n```\n\n### Analyzing Evolutionary Acceleration\n\nTo analyze whether a specific locus is undergoing evolutionary acceleration\n(i.e. evolving more rapidly than the neutral drift baseline), use `--analyze`.\nThis will compute scalar statistics (mean, min, max) for `phyloP` scores and\nprovide a heuristic boolean `is_accelerated` to simplify your evaluation.\n\n```bash\nuv run scripts\u002Fget_conservation.py --coordinates \"chr5:1045330-1046172\" --analyze --output \u002Ftmp\u002Faccelerated_cons.json\n```\n\n### Fetching Transcription Factor Binding Sites (TFBS)\n\nTo identify transcription factor binding sites for a given genomic interval.\nThis is useful for interpreting non-coding variants that might disrupt TF\nbinding.\n\nRun `scripts\u002Fget_tfbs.py` with `--coordinates` and `--tracks`. You can query\nmultiple tracks at once.\n\n```bash\nuv run scripts\u002Fget_tfbs.py --coordinates \"chr11:1001000-1010000\" --tracks encRegTfbsClustered --output \u002Ftmp\u002Ftfbs_encode.json\n```\n\nJASPAR tracks may return very large result sets. Use `--tf-filter` to keep only\nitems whose `TFName` field contains the given substring (case-insensitive):\n\n```bash\nuv run scripts\u002Fget_tfbs.py --coordinates \"chr6:36670000-36690000\" --tracks jaspar2024 --tf-filter TP53 --output \u002Ftmp\u002Ftp53_sites.json\n```\n\n#### Common Verified Tracks (hg38)\n\n-   **ENCODE**: `encRegTfbsClustered` (TF Clusters)\n-   **JASPAR**: `jaspar2026`, `jaspar2024` (Predicted TFBS)\n-   **ReMap**: `ReMapTFs` (ChIP-seq Atlas)\n\n> [!CAUTION] Tracks like `jaspar` or `ReMap` without years are often \"container\"\n> tracks and will fail with a 400 error. Always use the specific subtrack name\n> (e.g., `jaspar2026`).\n\n### Listing Available Tracks\n\nTo list available tracks (such as different versions of JASPAR, or purely to\ndiscover what tracks exist for a particular genome assembly):\n\n```bash\nuv run scripts\u002Flist_tracks.py --search \"jaspar\" --output \u002Ftmp\u002Fjaspar_tracks.json\n```\n\nYou can also filter by functional group:\n\n```bash\nuv run scripts\u002Flist_tracks.py --group \"regulation\" --output \u002Ftmp\u002Fregulation_tracks.json\n```\n\n## Anti-Patterns\n\n*   **DON'T** query mammalian (`--collection mammal`) constraint if you are\n    explicitly looking for deep evolutionary roots across all vertebrates. Use\n    the default `vertebrate` collection.\n*   **DON'T** use this skill for determining the ancestral state reconstruction\n    of a nucleotide (this skill provides measures of *how much* sites have\n    changed, not *what* the ancestral nucleotide was).\n*   **DON'T** assume low conservation strictly means neutral\u002Fuseless sequence;\n    it could also reflect a high local mutation rate which conservation scores\n    alone cannot distinguish.\n*   **DON'T** print output on standard out, or run cat on output to files. The\n    output is too large. Use jq or write your own code to parse the output\n    files.\n*   **DON'T** use hg19 unless the user has explicitly asked for it. The default\n    should be to always use hg38.\n",{"data":34,"body":35},{"name":4,"description":6},{"type":36,"children":37},"root",[38,47,70,75,82,144,150,184,190,195,240,253,260,272,349,355,375,428,434,462,469,558,564,673,820,826,854,906,912,917,945,1004,1025,1092,1098,1161,1197,1203,1208,1257,1262,1311,1317,1396],{"type":39,"tag":40,"props":41,"children":43},"element","h1",{"id":42},"conservation-scores-tfbs-lookup-ucsc",[44],{"type":45,"value":46},"text","Conservation Scores & TFBS Lookup (UCSC)",{"type":39,"tag":48,"props":49,"children":50},"p",{},[51,53,60,62,68],{"type":45,"value":52},"This skill provides access to evolutionary constraint scores and conserved\nelements from the UCSC Genome Browser. It retrieves scores from the PHAST\npackage — specifically ",{"type":39,"tag":54,"props":55,"children":57},"code",{"className":56},[],[58],{"type":45,"value":59},"phastCons",{"type":45,"value":61}," (identifying functional blocks) and ",{"type":39,"tag":54,"props":63,"children":65},{"className":64},[],[66],{"type":45,"value":67},"phyloP",{"type":45,"value":69},"\n(measuring individual site constraint) — calculated from multiple alignments.",{"type":39,"tag":48,"props":71,"children":72},{},[73],{"type":45,"value":74},"Use this skill to determine if a non-coding variant hits a site that hasn't\nchanged since a common ancestor (which is a strong signal for pathogenicity) or\nto find conservation peaks across a regulatory element.",{"type":39,"tag":76,"props":77,"children":79},"h2",{"id":78},"prerequisites",[80],{"type":45,"value":81},"Prerequisites",{"type":39,"tag":83,"props":84,"children":85},"ol",{},[86,116],{"type":39,"tag":87,"props":88,"children":89},"li",{},[90,100,102,107,109,114],{"type":39,"tag":91,"props":92,"children":93},"strong",{},[94],{"type":39,"tag":54,"props":95,"children":97},{"className":96},[],[98],{"type":45,"value":99},"uv",{"type":45,"value":101},": Read the ",{"type":39,"tag":54,"props":103,"children":105},{"className":104},[],[106],{"type":45,"value":99},{"type":45,"value":108}," skill and follow its Setup instructions to ensure\n",{"type":39,"tag":54,"props":110,"children":112},{"className":111},[],[113],{"type":45,"value":99},{"type":45,"value":115}," is installed and on PATH.",{"type":39,"tag":87,"props":117,"children":118},{},[119,124,126,134,136,142],{"type":39,"tag":91,"props":120,"children":121},{},[122],{"type":45,"value":123},"User Notification",{"type":45,"value":125},": If .licenses\u002Fucsc_conservation_and_tfbs_LICENSE.txt\ndoes not already exist in the workspace root directory then (1) prominently\nnotify the user to check the terms at\n",{"type":39,"tag":127,"props":128,"children":132},"a",{"href":129,"rel":130},"https:\u002F\u002Fgenome.ucsc.edu\u002Fconditions.html",[131],"nofollow",[133],{"type":45,"value":129},{"type":45,"value":135}," and\n",{"type":39,"tag":127,"props":137,"children":140},{"href":138,"rel":139},"https:\u002F\u002Fgenome.ucsc.edu\u002FgoldenPath\u002Fhelp\u002Fapi.html",[131],[141],{"type":45,"value":138},{"type":45,"value":143},", then (2) create the file\nrecording the notification text and timestamp.",{"type":39,"tag":76,"props":145,"children":147},{"id":146},"core-rules",[148],{"type":45,"value":149},"Core Rules",{"type":39,"tag":151,"props":152,"children":153},"ul",{},[154,164,174],{"type":39,"tag":87,"props":155,"children":156},{},[157,162],{"type":39,"tag":91,"props":158,"children":159},{},[160],{"type":45,"value":161},"Use the Wrapper",{"type":45,"value":163},": ALWAYS execute the provided helper scripts to query the\ndatabase rather than accessing the database directly. The scripts\nautomatically enforce the required rate limit gracefully.",{"type":39,"tag":87,"props":165,"children":166},{},[167,172],{"type":39,"tag":91,"props":168,"children":169},{},[170],{"type":45,"value":171},"Large Output Handling",{"type":45,"value":173},": Always pass --output to redirect output to a\nfile. Parse it separately (using jq or your own code).",{"type":39,"tag":87,"props":175,"children":176},{},[177,182],{"type":39,"tag":91,"props":178,"children":179},{},[180],{"type":45,"value":181},"Notification",{"type":45,"value":183},": If this skill is used, ensure this is mentioned in the\noutput.",{"type":39,"tag":76,"props":185,"children":187},{"id":186},"utility-scripts",[188],{"type":45,"value":189},"Utility Scripts",{"type":39,"tag":48,"props":191,"children":192},{},[193],{"type":45,"value":194},"This skill includes scripts to query different types of genomic data from UCSC:",{"type":39,"tag":83,"props":196,"children":197},{},[198,212,226],{"type":39,"tag":87,"props":199,"children":200},{},[201,210],{"type":39,"tag":91,"props":202,"children":203},{},[204],{"type":39,"tag":54,"props":205,"children":207},{"className":206},[],[208],{"type":45,"value":209},"scripts\u002Fget_conservation.py",{"type":45,"value":211},": For Evolutionary Conservation scores\n(phyloP, phastCons).",{"type":39,"tag":87,"props":213,"children":214},{},[215,224],{"type":39,"tag":91,"props":216,"children":217},{},[218],{"type":39,"tag":54,"props":219,"children":221},{"className":220},[],[222],{"type":45,"value":223},"scripts\u002Fget_tfbs.py",{"type":45,"value":225},": For Transcription Factor Binding Sites (TFBS).",{"type":39,"tag":87,"props":227,"children":228},{},[229,238],{"type":39,"tag":91,"props":230,"children":231},{},[232],{"type":39,"tag":54,"props":233,"children":235},{"className":234},[],[236],{"type":45,"value":237},"scripts\u002Flist_tracks.py",{"type":45,"value":239},": For listing available tracks based on search\nor group constraints.",{"type":39,"tag":48,"props":241,"children":242},{},[243,245,251],{"type":45,"value":244},"Always use the ",{"type":39,"tag":54,"props":246,"children":248},{"className":247},[],[249],{"type":45,"value":250},"hg38",{"type":45,"value":252}," genome assembly by default, unless the user has specified\notherwise.",{"type":39,"tag":254,"props":255,"children":257},"h3",{"id":256},"fetching-conservation-for-specific-variants",[258],{"type":45,"value":259},"Fetching Conservation for Specific Variants",{"type":39,"tag":48,"props":261,"children":262},{},[263,265,270],{"type":45,"value":264},"To get the evolutionary constraint at a single base, or a list of specific\nbases. This is optimal for single nucleotide variants (SNVs). ",{"type":39,"tag":54,"props":266,"children":268},{"className":267},[],[269],{"type":45,"value":67},{"type":45,"value":271}," is the\nbest metric for individual bases.",{"type":39,"tag":273,"props":274,"children":279},"pre",{"className":275,"code":276,"language":277,"meta":278,"style":278},"language-bash shiki shiki-themes material-theme-lighter material-theme material-theme-palenight","uv run scripts\u002Fget_conservation.py --coordinates \"chr1:215867804\" \"chr1:215867823\" --output \u002Ftmp\u002Fcons_output.json\n","bash","",[280],{"type":39,"tag":54,"props":281,"children":282},{"__ignoreMap":278},[283],{"type":39,"tag":284,"props":285,"children":288},"span",{"class":286,"line":287},"line",1,[289,294,300,305,310,316,321,326,330,335,339,344],{"type":39,"tag":284,"props":290,"children":292},{"style":291},"--shiki-light:#E2931D;--shiki-default:#FFCB6B;--shiki-dark:#FFCB6B",[293],{"type":45,"value":99},{"type":39,"tag":284,"props":295,"children":297},{"style":296},"--shiki-light:#91B859;--shiki-default:#C3E88D;--shiki-dark:#C3E88D",[298],{"type":45,"value":299}," run",{"type":39,"tag":284,"props":301,"children":302},{"style":296},[303],{"type":45,"value":304}," scripts\u002Fget_conservation.py",{"type":39,"tag":284,"props":306,"children":307},{"style":296},[308],{"type":45,"value":309}," --coordinates",{"type":39,"tag":284,"props":311,"children":313},{"style":312},"--shiki-light:#39ADB5;--shiki-default:#89DDFF;--shiki-dark:#89DDFF",[314],{"type":45,"value":315}," \"",{"type":39,"tag":284,"props":317,"children":318},{"style":296},[319],{"type":45,"value":320},"chr1:215867804",{"type":39,"tag":284,"props":322,"children":323},{"style":312},[324],{"type":45,"value":325},"\"",{"type":39,"tag":284,"props":327,"children":328},{"style":312},[329],{"type":45,"value":315},{"type":39,"tag":284,"props":331,"children":332},{"style":296},[333],{"type":45,"value":334},"chr1:215867823",{"type":39,"tag":284,"props":336,"children":337},{"style":312},[338],{"type":45,"value":325},{"type":39,"tag":284,"props":340,"children":341},{"style":296},[342],{"type":45,"value":343}," --output",{"type":39,"tag":284,"props":345,"children":346},{"style":296},[347],{"type":45,"value":348}," \u002Ftmp\u002Fcons_output.json\n",{"type":39,"tag":254,"props":350,"children":352},{"id":351},"fetching-regions-and-conserved-elements",[353],{"type":45,"value":354},"Fetching Regions and Conserved Elements",{"type":39,"tag":48,"props":356,"children":357},{},[358,360,365,367,373],{"type":45,"value":359},"To identify \"conservation peaks\" across a non-coding regulatory element (like an\nenhancer) to see if an ISM-predicted importance peak aligns with evolutionary\nhistory. ",{"type":39,"tag":54,"props":361,"children":363},{"className":362},[],[364],{"type":45,"value":59},{"type":45,"value":366}," is best for functional windows due to HMM smoothing. The\n",{"type":39,"tag":54,"props":368,"children":370},{"className":369},[],[371],{"type":45,"value":372},"--conserved-elements",{"type":45,"value":374}," flag will also retrieve predefined blocks under extreme\nconstraint.",{"type":39,"tag":273,"props":376,"children":378},{"className":275,"code":377,"language":277,"meta":278,"style":278},"uv run scripts\u002Fget_conservation.py --coordinates \"chr8:11748914-11749085\" --conserved-elements --output \u002Ftmp\u002Fregion_cons.json\n",[379],{"type":39,"tag":54,"props":380,"children":381},{"__ignoreMap":278},[382],{"type":39,"tag":284,"props":383,"children":384},{"class":286,"line":287},[385,389,393,397,401,405,410,414,419,423],{"type":39,"tag":284,"props":386,"children":387},{"style":291},[388],{"type":45,"value":99},{"type":39,"tag":284,"props":390,"children":391},{"style":296},[392],{"type":45,"value":299},{"type":39,"tag":284,"props":394,"children":395},{"style":296},[396],{"type":45,"value":304},{"type":39,"tag":284,"props":398,"children":399},{"style":296},[400],{"type":45,"value":309},{"type":39,"tag":284,"props":402,"children":403},{"style":312},[404],{"type":45,"value":315},{"type":39,"tag":284,"props":406,"children":407},{"style":296},[408],{"type":45,"value":409},"chr8:11748914-11749085",{"type":39,"tag":284,"props":411,"children":412},{"style":312},[413],{"type":45,"value":325},{"type":39,"tag":284,"props":415,"children":416},{"style":296},[417],{"type":45,"value":418}," --conserved-elements",{"type":39,"tag":284,"props":420,"children":421},{"style":296},[422],{"type":45,"value":343},{"type":39,"tag":284,"props":424,"children":425},{"style":296},[426],{"type":45,"value":427}," \u002Ftmp\u002Fregion_cons.json\n",{"type":39,"tag":254,"props":429,"children":431},{"id":430},"lineage-specific-constraints",[432],{"type":45,"value":433},"Lineage-Specific Constraints",{"type":39,"tag":48,"props":435,"children":436},{},[437,439,445,447,453,455,460],{"type":45,"value":438},"You can control the evolutionary depth using the ",{"type":39,"tag":54,"props":440,"children":442},{"className":441},[],[443],{"type":45,"value":444},"--collection",{"type":45,"value":446}," flag. The\ndefault (",{"type":39,"tag":54,"props":448,"children":450},{"className":449},[],[451],{"type":45,"value":452},"vertebrate",{"type":45,"value":454},") uses the ",{"type":39,"tag":91,"props":456,"children":457},{},[458],{"type":45,"value":459},"100-vertebrate Multiz alignment",{"type":45,"value":461}," for both\nhg38 and hg19, matching the UCSC Genome Browser's default comparative genomics\ntracks.",{"type":39,"tag":463,"props":464,"children":466},"h4",{"id":465},"hg38-collections",[467],{"type":45,"value":468},"hg38 Collections",{"type":39,"tag":151,"props":470,"children":471},{},[472,501,529],{"type":39,"tag":87,"props":473,"children":474},{},[475,483,485,491,493,499],{"type":39,"tag":91,"props":476,"children":477},{},[478],{"type":39,"tag":54,"props":479,"children":481},{"className":480},[],[482],{"type":45,"value":452},{"type":45,"value":484}," (default): UCSC 100-vertebrate Multiz alignment. phyloP:\n",{"type":39,"tag":54,"props":486,"children":488},{"className":487},[],[489],{"type":45,"value":490},"phyloP100way",{"type":45,"value":492},", phastCons: ",{"type":39,"tag":54,"props":494,"children":496},{"className":495},[],[497],{"type":45,"value":498},"phastCons100way",{"type":45,"value":500},".",{"type":39,"tag":87,"props":502,"children":503},{},[504,513,515,521,522,528],{"type":39,"tag":91,"props":505,"children":506},{},[507],{"type":39,"tag":54,"props":508,"children":510},{"className":509},[],[511],{"type":45,"value":512},"mammal",{"type":45,"value":514},": Hiller Lab 470-way mammalian alignment. 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Use\nthe default ",{"type":39,"tag":54,"props":1339,"children":1341},{"className":1340},[],[1342],{"type":45,"value":452},{"type":45,"value":1344}," collection.",{"type":39,"tag":87,"props":1346,"children":1347},{},[1348,1352,1354,1360,1362,1367],{"type":39,"tag":91,"props":1349,"children":1350},{},[1351],{"type":45,"value":1327},{"type":45,"value":1353}," use this skill for determining the ancestral state reconstruction\nof a nucleotide (this skill provides measures of ",{"type":39,"tag":1355,"props":1356,"children":1357},"em",{},[1358],{"type":45,"value":1359},"how much",{"type":45,"value":1361}," sites have\nchanged, not ",{"type":39,"tag":1355,"props":1363,"children":1364},{},[1365],{"type":45,"value":1366},"what",{"type":45,"value":1368}," the ancestral nucleotide was).",{"type":39,"tag":87,"props":1370,"children":1371},{},[1372,1376],{"type":39,"tag":91,"props":1373,"children":1374},{},[1375],{"type":45,"value":1327},{"type":45,"value":1377}," assume low conservation strictly means neutral\u002Fuseless sequence;\nit could also reflect a high local mutation rate which conservation scores\nalone cannot distinguish.",{"type":39,"tag":87,"props":1379,"children":1380},{},[1381,1385],{"type":39,"tag":91,"props":1382,"children":1383},{},[1384],{"type":45,"value":1327},{"type":45,"value":1386}," print output on standard out, or run cat on output to files. The\noutput is too large. Use jq or write your own code to parse the output\nfiles.",{"type":39,"tag":87,"props":1388,"children":1389},{},[1390,1394],{"type":39,"tag":91,"props":1391,"children":1392},{},[1393],{"type":45,"value":1327},{"type":45,"value":1395}," use hg19 unless the user has explicitly asked for it. The default\nshould be to always use hg38.",{"type":39,"tag":1397,"props":1398,"children":1399},"style",{},[1400],{"type":45,"value":1401},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":1403,"total":1508},[1404,1419,1432,1452,1464,1479,1495],{"slug":1405,"name":1405,"fn":1406,"description":1407,"org":1408,"tags":1409,"stars":22,"repoUrl":23,"updatedAt":1418},"alphafold-database-fetch-and-analyze","retrieve and analyze AlphaFold protein structures","Retrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT), domain boundary analysis, or disorder assessment. Do not use if the user only has a protein name, gene name, or amino acid sequence — ask for a UniProt ID first.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1410,1413,1416,1417],{"name":1411,"slug":1412,"type":15},"Bioinformatics","bioinformatics",{"name":1414,"slug":1415,"type":15},"Genomics","genomics",{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:51.827211",{"slug":1420,"name":1420,"fn":1421,"description":1422,"org":1423,"tags":1424,"stars":22,"repoUrl":23,"updatedAt":1431},"alphagenome-single-variant-analysis","analyze genetic variant effects with AlphaGenome","Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API. Use when the user asks about non-coding variant effects, pathogenicity, clinical significance, disease associations, functional effects, gene expression changes, splicing disruption, or regulatory effects in promoters and enhancers. Also use for resolving biological terms to tissue\u002Fcell-type ontologies (UBERON\u002FCL) or analyzing variants in chr:pos:ref>alt format.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1425,1426,1427,1428],{"name":1411,"slug":1412,"type":15},{"name":20,"slug":21,"type":15},{"name":13,"slug":14,"type":15},{"name":1429,"slug":1430,"type":15},"RNA-seq","rna-seq","2026-07-12T07:51:39.494803",{"slug":1433,"name":1433,"fn":1434,"description":1435,"org":1436,"tags":1437,"stars":22,"repoUrl":23,"updatedAt":1451},"chembl-database","query ChEMBL database for bioactive molecules","Query the ChEMBL database for bioactive molecules, drug targets, bioactivity data, approved drugs, and chemical structures. Use when the user asks about compounds, targets, IC50\u002FKi values, drug mechanisms, or structure searches.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1438,1441,1444,1447,1450],{"name":1439,"slug":1440,"type":15},"ChEMBL","chembl",{"name":1442,"slug":1443,"type":15},"Chemistry","chemistry",{"name":1445,"slug":1446,"type":15},"Database","database",{"name":1448,"slug":1449,"type":15},"Pharmacology","pharmacology",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:35.544306",{"slug":1453,"name":1453,"fn":1454,"description":1455,"org":1456,"tags":1457,"stars":22,"repoUrl":23,"updatedAt":1463},"clinical-trials-database","query clinical trial data","Query ClinicalTrials.gov via APIv2. Use when you want to search for trials by condition, drug, location, status, or phase; retrieve trial details by NCT ID; check eligibility\u002Finclusion criteria; count trials across conditions or time periods; identify a sponsor's trial portfolio; find recruiting trials for patient matching.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1458,1461,1462],{"name":1459,"slug":1460,"type":15},"Clinical Trials","clinical-trials",{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:52:06.846705",{"slug":1465,"name":1465,"fn":1466,"description":1467,"org":1468,"tags":1469,"stars":22,"repoUrl":23,"updatedAt":1478},"clinvar-database","retrieve clinical significance from ClinVar database","Use when needing clinical significance, pathogenicity classifications (e.g., Pathogenic, Benign, VUS), clinical evidence rationales, or finding \"hard positive\" benchmark controls for human genomic variants.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1470,1473,1474,1477],{"name":1471,"slug":1472,"type":15},"ClinVar","clinvar",{"name":20,"slug":21,"type":15},{"name":1475,"slug":1476,"type":15},"Healthcare","healthcare",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:36.86094",{"slug":1480,"name":1480,"fn":1481,"description":1482,"org":1483,"tags":1484,"stars":22,"repoUrl":23,"updatedAt":1494},"credentials","manage and verify API credentials safely","Instructions for handling API keys and credentials safely, verifying their presence, and prompting the user to add them if missing using a safe protocol.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1485,1488,1491],{"name":1486,"slug":1487,"type":15},"Compliance","compliance",{"name":1489,"slug":1490,"type":15},"Operations","operations",{"name":1492,"slug":1493,"type":15},"Security","security","2026-07-12T07:52:17.355491",{"slug":1496,"name":1496,"fn":1497,"description":1498,"org":1499,"tags":1500,"stars":22,"repoUrl":23,"updatedAt":1507},"dbsnp-database","search genetic variants in dbSNP database","Use when you want to look up, map, and search for short genetic variants (SNPs, indels) in NCBI's dbSNP database. Resolves between rsIDs, genomic coordinates in VCF format, and HGVS strings. For an rsID, returns variant type, gene associations, clinical significance, allele frequencies, and genomic coordinates (GRCh38).\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1501,1502,1503,1506],{"name":1411,"slug":1412,"type":15},{"name":20,"slug":21,"type":15},{"name":1504,"slug":1505,"type":15},"NCBI","ncbi",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:33.054229",38,{"items":1510,"total":1508},[1511,1518,1525,1533,1539,1546,1552,1559,1571,1586,1597,1607],{"slug":1405,"name":1405,"fn":1406,"description":1407,"org":1512,"tags":1513,"stars":22,"repoUrl":23,"updatedAt":1418},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1514,1515,1516,1517],{"name":1411,"slug":1412,"type":15},{"name":1414,"slug":1415,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"slug":1420,"name":1420,"fn":1421,"description":1422,"org":1519,"tags":1520,"stars":22,"repoUrl":23,"updatedAt":1431},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1521,1522,1523,1524],{"name":1411,"slug":1412,"type":15},{"name":20,"slug":21,"type":15},{"name":13,"slug":14,"type":15},{"name":1429,"slug":1430,"type":15},{"slug":1433,"name":1433,"fn":1434,"description":1435,"org":1526,"tags":1527,"stars":22,"repoUrl":23,"updatedAt":1451},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1528,1529,1530,1531,1532],{"name":1439,"slug":1440,"type":15},{"name":1442,"slug":1443,"type":15},{"name":1445,"slug":1446,"type":15},{"name":1448,"slug":1449,"type":15},{"name":13,"slug":14,"type":15},{"slug":1453,"name":1453,"fn":1454,"description":1455,"org":1534,"tags":1535,"stars":22,"repoUrl":23,"updatedAt":1463},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1536,1537,1538],{"name":1459,"slug":1460,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"slug":1465,"name":1465,"fn":1466,"description":1467,"org":1540,"tags":1541,"stars":22,"repoUrl":23,"updatedAt":1478},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1542,1543,1544,1545],{"name":1471,"slug":1472,"type":15},{"name":20,"slug":21,"type":15},{"name":1475,"slug":1476,"type":15},{"name":13,"slug":14,"type":15},{"slug":1480,"name":1480,"fn":1481,"description":1482,"org":1547,"tags":1548,"stars":22,"repoUrl":23,"updatedAt":1494},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1549,1550,1551],{"name":1486,"slug":1487,"type":15},{"name":1489,"slug":1490,"type":15},{"name":1492,"slug":1493,"type":15},{"slug":1496,"name":1496,"fn":1497,"description":1498,"org":1553,"tags":1554,"stars":22,"repoUrl":23,"updatedAt":1507},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1555,1556,1557,1558],{"name":1411,"slug":1412,"type":15},{"name":20,"slug":21,"type":15},{"name":1504,"slug":1505,"type":15},{"name":13,"slug":14,"type":15},{"slug":1560,"name":1560,"fn":1561,"description":1562,"org":1563,"tags":1564,"stars":22,"repoUrl":23,"updatedAt":1570},"embl-ebi-ols","search biomedical ontologies in EMBL-EBI OLS","Query and search the EMBL-EBI Ontology Lookup Service (OLS) for biomedical ontology terms, definitions, and hierarchies across 250+ ontologies (e.g., GO, DOID, HP). Use when the user asks to search for terms, retrieve details, navigate hierarchies (parents, children, ancestors), look up properties and individuals, get autocomplete suggestions, or access ontology metadata and statistics.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1565,1566,1569],{"name":1411,"slug":1412,"type":15},{"name":1567,"slug":1568,"type":15},"Ontology","ontology",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:59.368324",{"slug":1572,"name":1572,"fn":1573,"description":1574,"org":1575,"tags":1576,"stars":22,"repoUrl":23,"updatedAt":1585},"encode-ccres-database","query ENCODE regulatory and experimental data","Query the ENCODE Registry of cis-Regulatory Elements (cCREs) via the SCREEN GraphQL API, or make custom queries to the ENCODE Portal REST API for experiments and files (ChIP-seq peaks, etc.). Use when you want to query regulatory annotations or raw experimental data across human cell types.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1577,1578,1581,1582],{"name":1411,"slug":1412,"type":15},{"name":1579,"slug":1580,"type":15},"GraphQL","graphql",{"name":13,"slug":14,"type":15},{"name":1583,"slug":1584,"type":15},"REST API","rest-api","2026-07-12T07:52:10.597139",{"slug":1587,"name":1587,"fn":1588,"description":1589,"org":1590,"tags":1591,"stars":22,"repoUrl":23,"updatedAt":1596},"ensembl-database","query genomic and protein data from Ensembl","Query the Ensembl database to resolve gene, transcript, and protein IDs, fetch genomic or protein sequences, retrieve gene structures (exons), and get variant consequence and effect predictions (VEP). Use this skill as a primary ID translator, genomic sequence database and variant effect prediction tool.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1592,1593,1594,1595],{"name":1411,"slug":1412,"type":15},{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:41.645835",{"slug":1598,"name":1598,"fn":1599,"description":1600,"org":1601,"tags":1602,"stars":22,"repoUrl":23,"updatedAt":1606},"foldseek-structural-search","perform 3D protein structural searches","Performs 3D structural searches of proteins against various databases (PDB, AlphaFold, CATH, MGnify, etc.) using the Foldseek API. Use ONLY when the user provides a physical 3D coordinate file (.cif, .mmcif, or .pdb) and wants to find structurally similar proteins. Do NOT use if the user only provides a protein sequence, gene name, or UniProt ID.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1603,1604,1605],{"name":1411,"slug":1412,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:52:09.354992",{"slug":1608,"name":1608,"fn":1609,"description":1610,"org":1611,"tags":1612,"stars":22,"repoUrl":23,"updatedAt":1617},"gnomad-database","query genetic variant data from gnomAD","Query the Genome Aggregation Database (gnomAD). Use when determining the rarity or allele frequency of specific genetic variants, retrieving gene constraint metrics (pLI, LOEUF) to assess loss-of-function intolerance, finding variants in a genomic region or gene, or querying structural variants. Don't use for analyzing individual patient genomes, tracking somatic mutations in cancer (use COSMIC), or requesting raw sequencing reads (use ENA).\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1613,1614,1615,1616],{"name":1411,"slug":1412,"type":15},{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:38.213009"]