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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/main/tools/halla commit 5cd01ad3808dff1ce4aae231706cbe2225079a04
author iuc
date Wed, 05 Nov 2025 09:37:19 +0000
parents
children
files halla.xml test-data/X_16_100.txt test-data/Y_16_100.txt test-data/all_associations.tsv test-data/association_1.pdf test-data/sig_clusters.tsv
diffstat 6 files changed, 532 insertions(+), 0 deletions(-) [+]
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/halla.xml	Wed Nov 05 09:37:19 2025 +0000
@@ -0,0 +1,222 @@
+<tool id="halla" name="HAllA" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@" license="MIT">
+    <description>Hierarchical All-against-All association</description>
+    <macros>
+        <token name="@TOOL_VERSION@">0.8.40</token>
+        <token name="@VERSION_SUFFIX@">0</token>
+        <token name="@PROFILE@">24.0</token>
+    </macros>
+    <xrefs>
+        <xref type="bio.tools"></xref>
+    </xrefs>
+    <requirements>
+        <requirement type="package" version="@TOOL_VERSION@">halla</requirement>
+    </requirements>
+    <version_command><![CDATA[halla --version]]></version_command>
+    <command detect_errors="exit_code"><![CDATA[
+        halla
+            -x '$x'
+            --x_dataset_label 
+            #if $x_dataset_label
+                '$x_dataset_label'
+            #else
+                '$x.element_identifier'
+            #end if
+            -y '$y'
+            --y_dataset_label 
+            #if $y_dataset_label
+                '$y_dataset_label'
+            #else
+                '$y.element_identifier'
+            #end if
+            $alla
+            --max_freq_thresh $max_freq_thresh
+            #if $transform_data_funcs
+                --transform_data_funcs
+                #for $foo in $transform_data_funcs
+                    $foo
+                #end for
+            #end if
+            $disable_bypass_discretization_if_possible
+            #if $discretize_func
+                --discretize_func $discretize_func
+            #end if
+            #if $discretize_num_bins
+                --discretize_num_bins $discretize_num_bins
+            #end if
+            --pdist_metric $pdist_metric
+            $sim2dist_disable_abs
+            --linkage_method $linkage_method
+            --permute_func $permute_func
+            --permute_iters $permute_iters
+            $disable_permute_speedup
+            --fdr_alpha $fdr_alpha
+            --fdr_method $fdr_method
+            --fnr_thresh $fnr_thresh
+            --rank_cluster $rank_cluster
+            #if $seed
+                --seed $seed
+            #end if
+            --block_num $block_num
+            $hallagram
+            $diagnostic_plot
+            -o output
+            --num_threads "\${GALAXY_SLOTS:-4}"
+    ]]></command>
+    <inputs>
+        <param argument="-x" type="data" format="tabular" label="Dataset X" help="Tabular dataset with p features/rows and n samples/columns" />
+        <param argument="-y" type="data" format="tabular" label="Dataset Y" help="Tabular dataset with d features/rows and n samples/columns" />
+        <param argument="--alla" type="boolean" truevalue="--alla" falsevalue="" checked="false" label="Use AllA instead of HAllA" help="HAllA uses a hierarchical approach for block association discovery on top of an existing all-against-all (AllA) association matrix. Use this option to skip the block association step." />
+        <param argument="--max_freq_thresh" type="float" min="0" max="1" value="1" label="Maximum frequency" help="features with max frequences >= the threshold will be removed" />
+        <param argument="--transform_data_funcs" type="select" optional="true" multiple="true" label="Continuous data transformation function">
+            <option value="zscore">zscore</option>
+            <option value="rank">rank</option>
+            <option value="quantile">quantile</option>
+        </param>
+        
+        <param argument="--disable_bypass_discretization_if_possible" type="boolean" truevalue="--disable_bypass_discretization_if_possible" falsevalue="" checked="false" label="Discretize even if all features are continuous" help="By default discritization is bypassed if all features are continuous" />
+        <param argument="--discretize_func" type="select" optional="true" label="Discretization function">
+            <option value="quantile">quantile</option>
+            <option value="kmeans">kmeans</option>
+            <option value="uniform">uniform</option>
+            <option value="jenks">jenks</option>
+        </param>
+        <param argument="--discretize_num_bins" type="integer" min="0" value="" optional="true" label="Discretization - number of bins"/>
+
+        <param argument="--pdist_metric" type="select" label="Distance/similarity metric" help="default: spearman for continuous data, If there is at least one categorical variable in either dataset, HAllA will shift to Normalized Mutual Information (NMI) as an alternative similarity measure.">
+            <option value="spearman" selected="true">Spearman</option>
+            <option value="pearson">Pearson</option>
+            <option value="dcor">Distance correlation</option>
+            <option value="mi">mutual information</option>
+            <option value="nmi">normalized mutual information</option>
+            <option value="xicor">xi correlation</option>
+        </param>
+
+        <param argument="--sim2dist_disable_abs" type="boolean" truevalue="--sim2dist_disable_abs" falsevalue="" checked="false" label="Hierarchical clustering - disable setting similarity scores as absolute when computing distance" />
+        <param argument="--linkage_method" type="select" label="Hierarchical clustering linkage method" help="see help below">
+            <option value="single">single</option>
+            <option value="complete">complete</option>
+            <option value="average" selected="true">average</option>
+            <option value="weighted">weighted</option>
+            <option value="centroid">centroid</option>
+            <option value="median">median</option>
+            <option value="ward">ward</option>
+        </param>
+
+        <param argument="--permute_func" type="select" label="P-value approximation function" help=" in the p-value permutation test">
+            <option value="gpd">gdp</option>
+            <option value="ecdf">ecdf</option>
+        </param>
+        <param argument="--permute_iters" type="integer" min="0" value="1000" label="Number of iterations in the p-value permutation test"/>
+        <param argument="--disable_permute_speedup" type="boolean" truevalue="--disable_permute_speedup" falsevalue="" checked="false" label="Do not break early in the permutation test if p-value is insignificant"/>
+        <!-- \-\-force_permutations  If turned on, force permutation testing -->
+
+        <param argument="--fdr_alpha" type="float" min="0" max="1" value="0.05" label="FDR threshold"/>
+        <param argument="--fdr_method" type="select" label="FDR method" help="see help below">
+            <option value="bonferroni">bonferroni: one-step correction</option>
+            <option value="sidak">sidak: one-step correction</option>
+            <option value="holm-sidak">holm-sidak: </option>
+            <option value="holm">holm: </option>
+            <option value="simes-hochberg">simes-hochberg: </option>
+            <option value="hommel">hommel: </option>
+            <option value="fdr_bh" selected="true">fdr_bh: Benjamini/Hochberg (non-negative)</option>
+            <option value="fdr_by">fdr_by: Benjamini/Yekutieli (negative)</option>
+            <option value="fdr_tsbh">fdr_tsbh: two stage fdr correction (non-negative)</option>
+            <option value="fdr_tsbky">fdr_tsbky: two stage fdr correction (non-negative)</option>
+        </param>
+        <param argument="--fnr_thresh" type="float" min="0" max="1" value="0.05" label="FNR threshold"/>
+        <param argument="--rank_cluster" type="select" label="Procedure to rank cluster using the p-values within the cluster">
+            <option value="best" selected="true">best</option>
+            <option value="average">average</option>
+        </param>
+        <param argument="--seed" type="integer" value="" optional="true" label="Randomization seed" />
+        
+        <param argument="--hallagram" type="boolean" truevalue="--hallagram" falsevalue="--no_hallagram" checked="true" label="Generate hallagram" />
+        <param argument="--x_dataset_label" type="text" label="Hallagram/clustermap: label for X dataset" help="By default the dataset identifier is used"/>
+        <param argument="--y_dataset_label" type="text" label="Hallagram/clustermap: label for Y dataset" help="By default the dataset identifier is used"/>
+        <param argument="--block_num" type="integer" min="-1" value="-1" label="Number of top clusters in hallagram" help="-1: show all clusters"/>
+
+        <param argument="--diagnostic_plot" type="boolean" truevalue="--diagnostic_plot" falsevalue="" checked="false" label="Generates diagnostic plot" />
+    </inputs>
+    <outputs>
+        <data name="sig_clusters" format="tabular" from_work_dir="output/sig_clusters.txt" label="${tool.name} on ${on_string}: block associations"/> 
+        <data name="all_associations" format="tabular" from_work_dir="output/all_associations.txt" label="${tool.name} on ${on_string}: all associations"/> 
+        <data name="hallagram_out" format="pdf" from_work_dir="output/hallagram.pdf" label="${tool.name} on ${on_string}: hallagram">
+            <filter>hallagram is True</filter>
+        </data>
+        <collection name="diagnostic_plot_out" format="pdf" type="list" label="${tool.name} on ${on_string}: diagnostic plots">
+            <discover_datasets pattern="(?P&lt;designation&gt;association_.*)\.pdf" format="pdf" directory="output/diagnostic/" />
+            <filter>diagnostic_plot is True</filter>
+        </collection>
+    </outputs>
+    <tests>
+        <test expect_num_outputs="3">
+            <param name="x" value="X_16_100.txt"/>
+            <param name="y" value="Y_16_100.txt"/>
+            <param name="seed" value="42"/>
+            <output name="sig_clusters" value="sig_clusters.tsv"/>
+            <output name="all_associations" value="all_associations.tsv"/>
+        </test>
+        <test expect_num_outputs="3">
+            <param name="x" value="X_16_100.txt"/>
+            <param name="y" value="Y_16_100.txt"/>
+            <param name="seed" value="42"/>
+            <param name="hallagram" value="false"/>
+            <param name="diagnostic_plot" value="true"/>
+            <output name="sig_clusters" value="sig_clusters.tsv"/>
+            <output name="all_associations" value="all_associations.tsv"/>
+            <output_collection name="diagnostic_plot_out" type="list" count="18">
+                <element name="association_1" value="association_1.pdf"/>
+            </output_collection>
+        </test>
+    </tests>
+    <help><![CDATA[
+
+.. class:: infomark
+
+**What it does**
+
+HAllA (Hierarchical All-against-All association) is a method for finding blocks of associated features in high-dimensional datasets
+measured from a common set of samples. HAllA operates by 
+
+1. optionally discretizing mixed continuous and categorical features to a uniform representation
+2. hierarchically clustering each dataset separately to generate a pair of data hierarchies,
+3. performing all-against-all association testing between features across two datasets using robust measures of correlation,
+4. determining the statistical significance of individual associations by permutation testing, and
+5. iteratively subdividing the space of significant all-against-all correlations into blocks of densely associated occurring as clusters in the original datasets.
+
+Tutorial https://github.com/biobakery/biobakery/wiki/halla
+
+Usage
+.....
+
+**Input**
+
+Data in scientific studies often come paired in the form of two high-dimensional datasets, where the dataset 
+X (with p features/rows and n samples/columns) are assumed to be p predictor variables (or features) measured
+on n samples that give rise to d response variables contained in the dataset Y (with d features/rows and n samples/columns).
+Note that column i of X is sampled jointly with column i of Y, so that X and Y are aligned.
+
+**Output**
+
+HAllA reports significant associations between clusters of related features ("block associations").
+Each block association is characterized by a cluster from the first dataset, a cluster from the second dataset,
+and measures of statistical significance and effect size (p-value, q-value, and similarity score) for the cluster's
+component pairwise associations.
+
+- **block associations** which reports block associations between the two datasets' features
+- **all associations** which reports the pairwise similarity scores for all features across the two datasets
+- **hallagram** graphical representation discovered block associations
+- **diagnostic plots** (optional)lattice plot showing the pairwise associations between microbiome features and metadata for each significant cluster. 
+
+**Notes**
+
+Details on the available: 
+
+- Hierarchical clustering linkage methods https://docs.scipy.org/doc/scipy/reference/generated/scipy.cluster.hierarchy.linkage.html
+- FDR methods https://www.statsmodels.org/dev/generated/statsmodels.stats.multitest.multipletests.html
+
+    ]]></help>
+    <citations>
+        <citation type="doi">10.1093/bioinformatics/btac232</citation>
+    </citations>
+</tool>
\ No newline at end of file
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/X_16_100.txt	Wed Nov 05 09:37:19 2025 +0000
@@ -0,0 +1,17 @@
+#	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26	27	28	29	30	31	32	33	34	35	36	37	38	39	40	41	42	43	44	45	46	47	48	49
+X0	-0.752661407416	-0.918564669907	0.867973031552	-0.344217393007	0.176071481294	0.470336662896	-0.157686338276	1.05167008445	0.689470274209	-0.33905439878	-0.311695315143	-0.659036288578	1.14979015157	0.429876223193	1.17820655936	0.433771188242	-0.415625966089	-0.0127890343016	0.952624550459	-0.0249271086321	-0.383170620213	-0.056344805918	-0.839590095453	0.202001508751	-1.02406307909	0.590253756196	-0.242838142659	-0.825135868101	0.261567347433	0.0952221542582	0.727226821385	-0.510006970791	-0.373673323097	0.62414974331	-0.0743895919927	-0.144367672867	0.111133779396	0.202966084129	0.254165841661	-0.414329668297	-1.09637185127	-0.735756833148	0.119658003807	-0.0643551945148	1.24815216171	0.292103993414	0.545077780116	0.598053508941	0.216830922262	0.149859639397
+X1	-0.415741639248	-2.3673574489	0.152426444389	0.257252045105	-1.01851734557	0.014186787446	-0.409629061276	0.585199495883	0.924380372419	-0.514556750566	-0.647772199052	-0.922567676199	0.128753047604	0.316261419646	0.409727866952	0.343511134753	0.31192025355	-0.162462866131	0.164622112273	-0.57456094604	-0.93543283768	1.07323895211	-0.726789505168	0.670130774131	-1.27730215533	1.3234449245	-0.0724950049607	-1.17143739824	0.46722477098	-0.863345085351	1.05426596101	-1.32949555347	0.117426354699	0.371808011425	0.487089743838	-0.425257486656	0.162086963064	-0.273981043621	0.990835516779	-1.254031838	-1.35435258539	-1.58433874061	1.45777123794	0.136699387104	1.53155607984	0.711717077163	0.447309243631	0.174971237948	0.710838094731	-0.629215051407
+X2	0.791673792245	-2.03647345238	0.780365492828	0.510881684986	-0.862456010483	0.40394438953	0.244774997879	0.125187263784	0.687151962199	-0.239055308112	-0.0823663471734	-1.33645483151	0.28236242504	0.232559489109	-0.331844528123	0.560961268891	0.0138275126926	-0.7358854203	0.398630967456	-0.193431955693	-0.207077598105	1.11865881048	-0.81552699356	0.949644992394	-0.624641397765	2.30214156598	-0.39114862501	-0.708661818755	0.455164877324	0.491833191179	0.101429299473	-1.56319921777	-0.21127509045	-0.456555865617	-0.266242791077	-0.0272560058959	0.35297951904	-0.776394737448	0.381303152198	-1.16427332622	-1.24645195189	-0.949128444714	1.73645826487	0.726264624413	1.88637611852	0.151989312674	2.06187405418	1.41476180569	0.55582132117	-0.624351263456
+X3	1.1647811655	-0.624694695722	-0.959727323908	-0.793964006562	-0.762799687657	0.228637880054	0.574115616205	0.265912772025	0.0811089486813	-0.252703019531	0.482466414129	0.437482658219	-0.190720472561	0.174239237169	0.334968226557	-0.276186508904	-0.048571170699	0.400273469771	0.256380172699	-0.570854764787	0.772719599408	0.204025415358	0.378213376839	0.389076866621	-0.0499399181531	-0.0527919870563	-1.01870977321	-0.0509762802532	1.11700492093	-0.293690603014	-0.907976675281	-0.321035293175	-0.0380166077435	0.46982800732	-0.0700824872008	-0.536481130139	0.0231175009181	0.293302093671	-0.790746399561	-1.25942410821	0.734813800421	-1.40217324553	0.272768378921	-0.989646564	0.313836895559	-0.0710953312162	-1.30526375691	-0.0651109589948	-0.701177665296	-0.327242171223
+X4	1.13000089353	-0.295492738951	-0.28588219819	-0.894313944054	-0.493003250635	0.188994585073	0.142849473684	0.517831362501	-0.897131625743	0.153552778878	0.137582823336	0.135538171151	0.79001691825	0.645345039667	0.57617371919	0.635882339411	0.14951995232	0.0908996306219	0.785311311727	0.36024922676	-0.0138239963564	1.06743928568	0.787067436404	1.72569418691	-0.484739906328	0.116726951105	-1.59462082255	-0.837497247206	-0.19556638667	-0.260254893154	-1.48679273212	-1.04664194627	-1.26228055409	0.444746774169	0.535600110246	-0.63034255189	-0.215021257116	0.368101145927	-0.412598461846	-1.14426652493	0.195103994496	-1.50354864278	0.516731578272	-0.811820395594	1.29161467084	-0.429204198709	-1.5871434852	-0.697075839897	-0.748728422073	-0.498309255418
+X5	1.28341023251	-0.394794554133	1.13874487556	-0.908411557787	-0.175941596659	-0.0253405249772	0.0143739290746	-0.621657076187	-1.0346514614	0.549098537381	-0.478999755844	-0.16201549644	-0.0494926847198	0.00493951746595	1.03518419037	0.327711011096	0.504447831476	-0.53063756932	0.857817657687	1.48347131607	-0.158696772079	2.37901935122	0.120208882063	2.01363475659	0.805450564557	1.31483927204	-2.37252636337	-1.32842428991	1.00407273332	-0.339578461221	-0.65724522256	-1.7639088994	-1.12807258674	0.851831062097	0.00497915886246	-0.83358776063	-0.426896175714	1.02930868042	0.174726779314	-0.484855118747	0.437345490418	-1.37354832615	1.76076479285	-1.4599124935	1.27040184088	-0.798062355365	-2.4591496821	0.621778201413	-0.584479375754	-0.526087935063
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/Y_16_100.txt	Wed Nov 05 09:37:19 2025 +0000
@@ -0,0 +1,17 @@
+#	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26	27	28	29	30	31	32	33	34	35	36	37	38	39	40	41	42	43	44	45	46	47	48	49
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/all_associations.tsv	Wed Nov 05 09:37:19 2025 +0000
@@ -0,0 +1,257 @@
+X_features	Y_features	association	p-values	q-values
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Binary file test-data/association_1.pdf has changed
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/sig_clusters.tsv	Wed Nov 05 09:37:19 2025 +0000
@@ -0,0 +1,19 @@
+cluster_rank	cluster_X	cluster_Y	best_adjusted_pvalue
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