--- a/seurat_find_markers.xml	Wed Apr 03 11:17:29 2019 -0400
+++ b/seurat_find_markers.xml	Mon Nov 25 06:09:57 2019 -0500
@@ -1,4 +1,4 @@
-<tool id="seurat_find_markers" name="Seurat FindMarkers" version="2.3.1+galaxy1">
+<tool id="seurat_find_markers" name="Seurat FindMarkers" version="@SEURAT_VERSION@_@VERSION@+galaxy0">
     <description>find markers (differentially expressed genes)</description>
     <macros>
         <import>seurat_macros.xml</import>
@@ -8,7 +8,7 @@
     <command detect_errors="exit_code"><![CDATA[
 seurat-find-markers.R
 
---input-object-file '$input'
+@INPUT_OBJECT@
 --output-text-file output.txt
 
 #if $genes_use:
@@ -49,7 +49,7 @@
 ]]></command>
 
     <inputs>
-        <param name="input" type="data" format="rdata" label="RDS object" />
+        <expand macro="input_object_params"/>
         <expand macro="genes-use-input"/>
         <param name="logfc_threshold" label="LogFC logfc_threshold" optional="true" argument="--logfc-threshold" type="float" help="Limit testing to genes which show, on average, at least X-fold difference (log-scale) between the two groups of cells. Default is 0.25 Increasing logfc.threshold speeds up the function, but can miss weaker signals."/>
         <param name="max_cells_per_ident" label="Max cells per ident" optional="true" argument="--max-cells-per-ident" type="integer" help="Down sample each identity class to a max number. Default is no downsampling. Not activated by default (set to Inf)."/>
@@ -74,7 +74,7 @@
     </inputs>
 
     <outputs>
-        <data name="output" format="txt" from_work_dir="output.txt" label="${tool.name} on ${on_string}: Text file"/>
+        <data name="output" format="csv" from_work_dir="output.txt" label="${tool.name} on ${on_string}: Text file"/>
     </outputs>
 
     <tests>
@@ -88,12 +88,17 @@
 
 **What it does**
 
-Seurat_ is a toolkit for quality control, analysis, and exploration of single cell RNA sequencing data.
-It is developed and maintained by the `Satija Lab`_ at NYGC. Seurat aims to enable users to identify and
-interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse
-types of single cell data.
+This tool finds markers (differentially expressed genes) for each of the identity classes in a dataset.
+It outputs a text file containing a ranked list of putative markers, and associated statistics (p-values, ROC score, etc.)
 
-This tool finds markers (differentially expressed genes) for each of the identity classes in a dataset. It outputs a text file containing a ranked list of putative markers, and associated statistics (p-values, ROC score, etc.)
+p-value adjustment is performed using bonferroni correction based on the total
+number of genes in the dataset. Other correction methods are not recommended,
+as Seurat pre-filters genes using the arguments above, reducing the number of
+tests performed. Lastly, as Aaron Lun has pointed out, p-values should be
+interpreted cautiously, as the genes used for clustering are the same genes
+tested for differential expression.
+
+@SEURAT_INTRO@
 
 -----