Update the KEGG assets to kegg120

CHANGELOG.md

@@ -1,5 +1,11 @@
 # Changelog
 
+## Unreleased
+
+### Data
+
+* The KEGG assets are the `kegg120` release of `toolbox-assets` (was: `kegg118`), and `fetchToolboxAsset` reads the manifest `manifest-v4`.
+
 ## 3.0.0b2 — 2026-11-01
 
 Second beta toward 3.0. Changes below are relative to 3.0.0b1.

src/installation/fetchToolboxAsset.m

@@ -9,7 +9,7 @@
 % supplies the release tag and the asset name.
 %
 % A download is checked against the SHA-256 checksum that the
-% toolbox-assets manifest (release manifest-v3) lists for it. A file whose
+% toolbox-assets manifest (release manifest-v4) lists for it. A file whose
 % checksum differs is deleted and an error is raised. An asset that the
 % manifest does not list, or a manifest that cannot be read, gives a
 % warning and the file is kept unchecked.
@@ -19,9 +19,9 @@
 % destDir : char
 %     directory to download into (created if it does not exist yet).
 % releaseTag : char
-%     the toolbox-assets release tag, for example 'kegg118'.
+%     the toolbox-assets release tag, for example 'kegg120'.
 % assetName : char
-%     the release asset file name, for example 'kegg118_core.tar.gz'.
+%     the release asset file name, for example 'kegg120_core.tar.gz'.
 %
 % Returns
 % -------
@@ -75,7 +75,7 @@
 sha='';
 if isempty(manifest)
     try
-        manifest=webread('https://github.com/CompMetEng/toolbox-assets/releases/download/manifest-v3/manifest.json', ...
+        manifest=webread('https://github.com/CompMetEng/toolbox-assets/releases/download/manifest-v4/manifest.json', ...
             weboptions('ContentType','json','Timeout',30));
     catch ME
         warning('RAVEN:fetchToolboxAsset:manifest','Cannot read the toolbox-assets manifest: %s',ME.message);

src/reconstruction/kegg/KEGG_VERSION.md

@@ -1,4 +1,4 @@
-kegg118
+kegg120
 
 This is the toolbox-assets release tag that every KEGG-artefact download in
 this folder reads from --- getModelFromKEGG's core reference-model/table

src/reconstruction/kegg/getKEGGModelForOrganism.m

@@ -26,8 +26,8 @@
 %     case, cutOff, minScoreRatioKO, minScoreRatioG and dataDir are not
 %     used (default []).
 % dataDir : char
-%     directory of the HMM library, named kegg118_prokaryotes or
-%     kegg118_eukaryotes. The name gives the KEGG version and whether the
+%     directory of the HMM library, named kegg120_prokaryotes or
+%     kegg120_eukaryotes. The name gives the KEGG version and whether the
 %     HMMs were trained on pro- or eukaryotic sequences, and matches the
 %     published HMM library it is paired with. The prebuilt concatenated KO
 %     HMM library (dataDir.hmm) is downloaded from the corresponding
@@ -96,7 +96,7 @@
 %   2. From protein homology (fastaFile supplied). The query proteome is
 %      searched, in a single hmmsearch, against a prebuilt KEGG-version- and
 %      domain-specific concatenated KO HMM library (for example
-%      kegg118_eukaryotes), downloaded from the corresponding toolbox-assets
+%      kegg120_eukaryotes), downloaded from the corresponding toolbox-assets
 %      release if not already present in dataDir. Hits are filtered by cutOff,
 %      minScoreRatioKO and minScoreRatioG into a KO-gene matrix, from which the
 %      model is built (spontaneous reactions without genes are kept if

src/reconstruction/kegg/keggDataVersion.m

@@ -9,7 +9,7 @@
 % Returns
 % -------
 % version : char
-%     the toolbox-assets release tag, for example 'kegg118'.
+%     the toolbox-assets release tag, for example 'kegg120'.
 
 ravenPath=findRAVENroot();
 versionFile=fullfile(ravenPath,'src','reconstruction','kegg','KEGG_VERSION.md');

src/reconstruction/kegg/readKEGGTable.m

@@ -7,7 +7,7 @@
 % Parameters
 % ----------
 % gzFile : char
-%     path to the gzipped TSV file, for example '.../kegg118_ko_reaction.tsv.gz'.
+%     path to the gzipped TSV file, for example '.../kegg120_ko_reaction.tsv.gz'.
 %
 % Returns
 % -------

tutorials/tutorial5.m

@@ -10,7 +10,7 @@
 % 
 % Start by downloading trained Hidden Markov Models for eukaryotes. This can
 % be done automatically or manually from the RAVEN Wiki in its GitHub
-% repository. In this tutorial, the archive "kegg118_eukaryotes" is picked for
+% repository. In this tutorial, the archive "kegg120_eukaryotes" is picked for
 % the automatic download. See the documentation in the RAVEN Wiki for more
 % information regarding preparation of such archive.
 % 
@@ -20,7 +20,7 @@
 % are for. This process takes up to 20-35 minutes in macOS, Unix systems and
 % 40-55 minutes in Windows, depending on your hardware and the size of
 % target organism proteome
-model=getKEGGModelForOrganism('sce','sce.fa','kegg118_eukaryotes','output',false,false,false,false,10^-30,0.8,0.3,-1);
+model=getKEGGModelForOrganism('sce','sce.fa','kegg120_eukaryotes','output',false,false,false,false,10^-30,0.8,0.3,-1);
 
 % The resulting model should contain around 1589 reactions, 1600
 % metabolites and 836 genes. Small variations are possible since it is an