--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/fastspar.xml	Thu Jun 19 21:51:32 2025 +0000
@@ -0,0 +1,102 @@
+<tool id="fastspar" name="FastSpar" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@">
+    <description>
+        correlation estimation for compositional data
+    </description>
+    <macros>
+        <import>macros.xml</import>
+    </macros>
+    <expand macro="biotools"/>
+    <expand macro="requirements"/>
+    <command detect_errors="exit_code"><![CDATA[
+        fastspar
+            --otu_table '$otu_table'
+            --iterations $iterations
+            --exclude_iterations $exclude_iterations
+            --threshold $threshold
+            --seed $seed
+            --correlation '$correlation'
+            --covariance '$covariance'
+            --threads \${GALAXY_SLOTS:-1}
+            ## Skip warning prompt and continue analysis even if the input contains OTUs with just one permutation.
+            --yes
+    ]]></command>
+    <inputs>
+        <param argument="--otu_table" type="data" format="tabular" label="Input OTU table"
+               help="The table must contain absolute OTU counts in plain tabular (TSV) format, with OTUs as rows and samples as columns. Do not include any metadata rows or columns."/>
+        <expand macro="fastspar_tool_parameters"/>
+        <param argument="--seed" type="integer" value="1" label="Random number seed"/>
+    </inputs>
+    <outputs>
+        <data name="correlation" format="tabular" label="${tool.name} on ${on_string}: median_correlation.tsv"/>
+        <data name="covariance" format="tabular" label="${tool.name} on ${on_string}: median_covariance.tsv"/>
+    </outputs>
+    <tests>
+        <test expect_num_outputs="2">
+            <param name="otu_table" ftype="tabular" value="fake_data.tsv"/>
+            <output name="correlation" file="fake_data_cor.tsv" compare="diff"/>
+            <output name="covariance" file="fake_data_cov.tsv" compare="diff"/>
+        </test>
+        <test expect_num_outputs="2">
+            <param name="otu_table" ftype="tabular" value="fake_data.tsv"/>
+            <param name="exclude_iterations" value="20"/>
+            <param name="threshold" value="0.2"/>
+            <output name="correlation" ftype="tabular">
+                <assert_contents>
+                    <has_n_columns n="51"/>
+                    <has_text text="1.0000"/>
+                </assert_contents>
+            </output>
+            <output name="covariance" ftype="tabular">
+                <assert_contents>
+                    <has_n_columns n="51"/>
+                    <has_text text="OTU ID"/>
+                </assert_contents>
+            </output>
+        </test>
+    </tests>
+    <help><![CDATA[
+What it does
+============
+
+FastSpar is a C++ implementation of the SparCC algorithm for estimating correlations from compositional data.
+This tool performs the **initial correlation and covariance matrix estimation** as the first step in the FastSpar pipeline.
+**If you also want to estimate p-values** you might want to use `fastspar_pvalues` with "Recalculate the correlation matrix".
+
+Required Inputs
+===============
+
+- **OTU table** (TSV format): Contains absolute OTU counts (not relative abundances). Must be a plain tabular file with samples in columns and OTUs in rows. Metadata is not supported.
+
+Main Parameters
+===============
+
+- **Iterations** (`--iterations`): Number of correlation estimation rounds. More iterations improve stability.
+- **Exclude iterations** (`--exclude_iterations`): Number of times highly correlated OTU pairs are removed.
+- **Correlation threshold** (`--threshold`): Correlation strength above which to exclude OTU pairs.
+- **Seed** (`--seed`): Random seed for reproducibility.
+
+Main Features
+===============
+
+- Efficient and fast computation of sparse correlations.
+- Customizable exclusion and thresholding strategy.
+- Designed to handle compositional count data from microbiome studies.
+
+Generated Outputs
+=================
+
+- `median_correlation.tsv`: Correlation matrix between all OTUs.
+- `median_covariance.tsv`: Covariance matrix between all OTUs.
+
+Additional Resources
+====================
+
+- FastSpar GitHub: [https://github.com/scwatts/fastspar]
+
+For a complete FastSpar analysis, follow up with:
+
+1. `fastspar_pvalues`: Estimate empirical p-values from bootstrap correlations.
+2. `fastspar_reduce`: Filter correlation and p-value matrices to produce sparse networks.
+    ]]></help>
+    <expand macro="citations"/>
+</tool>
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