cli.markdown modifications for github formatting

4 spaces for function --help
4 spaces for QIIME procedure
remove extra backslash

1 files changed, 29 insertions, 26 deletions

diff --git a/doc/cli.markdown b/doc/cli.markdown
index 3d7a636..587d014 100644
--- a/doc/cli.markdown
+++ b/doc/cli.markdown
@@ -12,11 +12,11 @@ Before running the quikr utility, you need to generate the sensing matrix.
 quikr\_train returns a custom sensing matrix that can be used with the quikr
 function.
 
-quikr\_train's arguments:
-  -i, --input, the database of sequences (fasta format)
-  -o, --output, the sensing matrix (text file)
-  -k, --kmer, specifiy wha size of kmer to use. (default value is 6)
-  -v, --verbose, verbose mode.
+    quikr_train's arguments:
+      -i, --input, the database of sequences (fasta format)
+      -o, --output, the sensing matrix (text file)
+      -k, --kmer, specifiy wha size of kmer to use. (default value is 6)
+      -v, --verbose, verbose mode.
 
 ### Example ###
 Here is an example on how to train a database. This uses the -z flag to compress
@@ -34,13 +34,13 @@ input FASTA file. You need to train a matrix or download a new matrix
 ### Usage ###
 quikr returns the solution vector as a csv file.
 
-quikr's arguments:
-  -f, --fasta, the sample's fasta file of NGS READS
-  -o, --output OTU\_FRACTION\_PRESENT, a vector representing the percentage of
-  database sequence's presence in sample (csv output)
-  -s, --sensing-matrix the sensing matrix. (generated by quikr\_train)
-  -l, --lambda, the lambda size. (the default lambda value is 10,000)
-  -k, --kmer, this specifies the size of the kmer to use (default is 6)
+    quikr's arguments:
+      -f, --fasta, the sample's fasta file of NGS READS
+      -o, --output OTU\_FRACTION\_PRESENT, a vector representing the percentage of
+          database sequence's presence in sample (csv output)
+      -s, --sensing-matrix the sensing matrix. (generated by quikr\_train)
+      -l, --lambda, the lambda size. (the default lambda value is 10,000)
+      -k, --kmer, this specifies the size of the kmer to use (default is 6)
 
 ## Multifasta\_to\_otu ##
 The Multifasta\_to\_otu tool is a handy wrapper for quikr which lets the user
@@ -61,19 +61,20 @@ with aspecified number of jobs. Otherwise python with run one job per cpu core.
   .fa are valid while .fna is NOT)
 
 ### Usage ###
-multifasta\_to\_otu's arguments:
-  -i, --input, the directory containing the samples' fasta files of
-  reads (note each fasta file should correspond to a separate sample)
-  -o, --otu-table, the OTU table, with OTU\_FRACTION\_PRESENT for each sample,
-  which is compatible with QIIME's convert\_biom.py (or sequence table if not
-  OTU's)
-  -s, --sensing-matrix, the sensing matrix
-  -f, --sensing-fasta, the fasta file database of sequences
-  -l, --lambda, specify what size of lambda to use (the default value is 10,000)
-  -k, --kmer, specify what size of kmer to use, (default value is 6)
-  -j, --jobs, specifies how many jobs to run at once, (default=number of CPUs)
-
-# Post-processing of Multifasta\_to\_otu  #
+
+    multifasta\_to\_otu's arguments:
+      -i, --input, the directory containing the samples' fasta files of
+      reads (note each fasta file should correspond to a separate sample)
+      -o, --otu-table, the OTU table, with OTU\_FRACTION\_PRESENT for each sample,
+      which is compatible with QIIME's convert\_biom.py (or sequence table if not
+      OTU's)
+      -s, --sensing-matrix, the sensing matrix
+      -f, --sensing-fasta, the fasta file database of sequences
+      -l, --lambda, specify what size of lambda to use (the default value is 10,000)
+      -k, --kmer, specify what size of kmer to use, (default value is 6)
+      -j, --jobs, specifies how many jobs to run at once, (default=number of CPUs)
+
+### Post-processing of Multifasta\_to\_otu  ###
 
 * Note: When making your QIIME Metadata file, the sample id's must match the
   sample fasta file prefix names
@@ -89,12 +90,14 @@ Pre-requisites:
 3. your-defined <qiime_metadata_file.txt>
 
 The QIIME procedue:
+
     convert_biom.py -i <quikr_otu_table.txt> -o <quikr_otu>.biom --biom_table_type="otu table"
     beta_diversity.py -i <quikr_otu>.biom -m weighted_unifrac -o beta_div -t <tree file> (example: rdp7_mafft.fasttree)>
     principal_coordinates.py -i beta_div/weighted_unifrac_<quikr_otu>.txt -o <quikr_otu_project_name>_weighted.txt
     make_3d_plots.py -i <quikr_otu_project_name>_weighted.txt -o <3d_pcoa_plotdirectory> -m <qiime_metadata_file>
 
-#### Broken Pipe Errors #### 
+
+#### Broken Pipe Errors ####
 Make sure that you have the count-kmers and probablilties-by-read in your
 $PATH, and that they are executable.