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README.md

@@ -352,7 +352,7 @@ The contents of the subdirectories are:
 
 ### <b>Step by step examples</b>
 
-#### Example 1 - <i>Cryptococcus</i>
+### Example 1 - <i>Cryptococcus</i>
 Below is a quick example describing how to compare a few select <i>Cryptococcus</i> genomes (<i>C. neoformans</i> var. <i>neoformans</i> strain [JEC21](https://www.ncbi.nlm.nih.gov/bioproject/PRJNA13856/), <i>C. gattii</i> strain [WM276](https://www.ncbi.nlm.nih.gov/bioproject/PRJNA13692/), <i>C. gattii</i> VGV strain [MF34](hhttps://www.ncbi.nlm.nih.gov/bioproject/PRJNA487802/), <i>C. decagattii</i> strain [7685027](https://www.ncbi.nlm.nih.gov/bioproject/PRJNA660466/), <i>C. deuterogattii</i> strain [R265](https://www.ncbi.nlm.nih.gov/bioproject/PRJNA395628/)) using annotation data available from the public NCBI [Genome](https://www.ncbi.nlm.nih.gov/genome/database) database.
 
 ##### Downloading annotation data from GenBank (NCBI):
@@ -691,7 +691,7 @@ Likewise, the total average sequence identity percentage listed in the PAF metri
 
 As a rule of thumb, pairwise alignments featuring lower sequence identity percentages will produce fewer and/or more fragmented collinear segments.
 
-#### Example 2 - Encephalitozoonidae
+### Example 2 - Encephalitozoonidae
 Below is a quick example describing how to compare a few select genomes from the Encephalitozoonidae (<i>Encephalitozoon/Ordospora</i> species <i>E. intestinalis</i> strain [ATCC 50506](https://www.ncbi.nlm.nih.gov/bioproject/PRJNA594722/), <i>E. hellem</i> strain [ATCC 50604](https://www.ncbi.nlm.nih.gov/bioproject/PRJNA594722/), <i>E. cuniculi</i> strain [ATCC 50602](https://www.ncbi.nlm.nih.gov/bioproject/PRJNA705735/), <i>O. colligata</i> strain [OC4](https://www.ncbi.nlm.nih.gov/bioproject/PRJNA210314/) and <i>O. pajunii</i> strain [FI-F-10](https://www.ncbi.nlm.nih.gov/bioproject/PRJNA630072/)) using annotation data from NCBI.
 
 The Encephalitozoonidae genomes in this example are highly collinear yet display a high level of sequence divergence. As such, they consitute a good case scenario to assess the benefits of using gene clusters to complement inferences based on pairwise genome alignments.