Small changes in README restructured text syntax.

README.rst

@@ -1,4 +1,3 @@
-
 pySCENIC
 ========
 
@@ -19,9 +18,11 @@ The pipeline has three steps:
 2. These regulons are refined by pruning targets that do not have an enrichment for a corresponding motif of the TF effectively separating direct from indirect targets based on the presence of cis-regulatory footprints.
 3. Finally, the original cells are differentiated and clustered on the activity of these discovered regulons.
 
+
 .. note::
     The most impactfull speed improvement is introduced by the arboretum_ package in step 1. This package provides an alternative to GENIE3 [3]_ called GRNBoost2. This package can be controlled from within pySCENIC.
 
+
 .. sidebar:: **Quick Start**
 
     * `Installation`_
@@ -45,9 +46,12 @@ Installation
 
 The lastest stable release of the **package** itself can be installed via :code:`pip install pyscenic`.
 
+
 .. caution::
+
     pySCENIC needs a python 3.5 or greater interpreter.
 
+
 You can also install the bleeding edge (i.e. less stable) version of the package directly from the source:
 
 .. code-block:: bash
@@ -121,6 +125,7 @@ dm6-5kb-upstream-full-tx_           Drosophila melanogaster     [TSS+5kb,full Tx
 .. _`MGI annotations`: http://pyscenic.aertslab.org/resources/motifs-v9-nr.mgi-m0.001-o0.0.tbl
 .. _`Flybase annotations`: http://pyscenic.aertslab.org/resources/motifs-v8-nr.flybase-m0.001-o0.0.tbl
 
+
 .. caution::
     These ranking databases are 1.1 Gb each so downloading them might take a while. An annotations file is typically 100Mb in size.
 
@@ -230,7 +235,7 @@ The first method to create the TF-modules is to select the best targets for each
 
 1. Targets with importance > the 50th percentile.
 2. Targets with importance > the 75th percentile
-2. Targets with importance > the 90th percentile.
+3. Targets with importance > the 90th percentile.
 
 The second method is to select the top targets for a given TF:
 

requirements.doc.txt

@@ -1,2 +1,3 @@
 sphinx
 sphinx_rtd_theme
+restructuredtext_lint