Update example script

Author: Francesco Beghini

example/bioconda-lefse_run.sh

@@ -3,9 +3,6 @@
 ## https://bitbucket.org/nsegata/lefse/src/54694b4b0d9e335ff1ecafff8db4f1e0cf7004da/example/run.sh?at=default&fileviewer=file-view-default
 ##
 ##
-## note: ensure script names below match those in the conda install directory, otherwise will error: 'not found':
-## scripts usually visible in ~/miniconda3/envs/lefse/bin/ if was installed to default directory
-## 
 
 
 # Download a 3-classes example (with subclasses and subjects) from huttenhower.sph.harvard.edu
@@ -14,7 +11,7 @@
 wget https://github.com/biobakery/biobakery/raw/master/demos/biobakery_demos/data/lefse/input/hmp_small_aerobiosis.txt -O hmp_aerobiosis_small.txt
 
 # As using LEfSe through bioconda, need to activate the LEfSe installation:
-source activate lefse
+conda activate lefse
 
 # Running the LEfSe commands with -h gives the list of available options
 
@@ -26,7 +23,7 @@ source activate lefse
 # the value -1 for them.
 # -o 1000000 scales the feature such that the sum (of the same taxonomic leve)
 # is 1M: this is done only for obtaining more meaningful values for the LDA score
-lefse-format_input.py hmp_aerobiosis_small.txt hmp_aerobiosis_small.in -c 1 -s 2 -u 3 -o 1000000
+lefse_format_input.py hmp_aerobiosis_small.txt hmp_aerobiosis_small.in -c 1 -s 2 -u 3 -o 1000000
 
 # run_lefse.py performs the actual statistica analysis
 #
@@ -35,33 +32,33 @@ lefse-format_input.py hmp_aerobiosis_small.txt hmp_aerobiosis_small.in -c 1 -s 2
 # can be listed using the -h option 
 run_lefse.py hmp_aerobiosis_small.in hmp_aerobiosis_small.res
 
-# lefse-plot_res.py visualizes the output
+# lefse_plot_res.py visualizes the output
 #
 # Plot the list of biomarkers with their effect size
 # Severak graphical options are available for personalizing the output
-lefse-plot_res.py hmp_aerobiosis_small.res hmp_aerobiosis_small.png
+lefse_plot_res.py hmp_aerobiosis_small.res hmp_aerobiosis_small.png
 
-# plot_cladogram.py visualizes the output on a hierarchical tree
+# lefse_plot_cladogram.py visualizes the output on a hierarchical tree
 #
 # Plot the representation of the biomarkers on the hierarchical tree
 # specified in the input data (using | in the name of the features)
 # In this case we will obtain the RDP taxonomy.
 # This is an early implementation of the module. I'm working on an improved version
 # that will be released independently from LEfSe
-lefse-plot_cladogram.py hmp_aerobiosis_small.res hmp_aerobiosis_small.cladogram.png --format png
+lefse_plot_cladogram.py hmp_aerobiosis_small.res hmp_aerobiosis_small.cladogram.png --format png
 
 # Create a directory for storing the raw-data representation of the discovered biomarkers
 mkdir biomarkers_raw_images
 
-# lefse-plot_features.py visualizes the raw-data features
+# lefse_plot_features.py visualizes the raw-data features
 #
 # The module for exporting the raw-data representation of the features.
 # With the default options we will obtain the images for all the features that are
 # detected as biomarkers
-lefse-plot_features.py hmp_aerobiosis_small.in hmp_aerobiosis_small.res biomarkers_raw_images/
+lefse_plot_features.py hmp_aerobiosis_small.in hmp_aerobiosis_small.res biomarkers_raw_images/
 
 ## Turn lefse back off
-source deactivate lefse
+conda deactivate lefse
 
 ## bonus: seasonal greetings
 # echo '~ Oíche Shamhna féile dhuit!'