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arpcard · Feb 6, 2024 · dc64bff · dc64bff
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diff --git a/README.rst b/README.rst
@@ -27,18 +27,17 @@ May 2023: Chan Zuckerberg ID (CZ ID) has implemented a web-based platform for RG
 
 **CARD reference sequences and significance cut-offs are under constant curation - as CARD curation evolves, the results of RGI evolve.**
 
- > `CARD Frequency Asked Questions <https://github.com/arpcard/FAQ>`_
-
- > `YouTube Video Lecture: Canadian Bioinformatics Workshops 2023 - Infectious Disease Genomic Epidemiology - Antimicrobial Resistant Gene (AMR) Analysis using CARD & RGI <https://www.youtube.com/watch?v=FvOCDlcYaTo&list=PL3izGL6oi0S8RG8vnwLXFznzJnKh8OR8F&index=6>`_
+* `CARD Frequency Asked Questions <https://github.com/arpcard/FAQ>`_
+* `YouTube Video Lecture: Canadian Bioinformatics Workshops 2023 - Infectious Disease Genomic Epidemiology - Antimicrobial Resistant Gene (AMR) Analysis using CARD & RGI <https://www.youtube.com/watch?v=FvOCDlcYaTo&list=PL3izGL6oi0S8RG8vnwLXFznzJnKh8OR8F&index=6>`_
 
 .. contents::
 
 Overview of RGI
 ===============
 
-* [Analyzing Genomes, Genome Assemblies, Metagenomic Contigs, or Proteomes](/docs/rgi_main.rst) (a.k.a. RGI main)
-* [Analyzing Metagenomic Reads](/docs/rgi_bwt.rst) (a.k.a. RGI bwt)
-* [K-mer Prediction of Pathogen-of-Origin for AMR Genes](/docs/rgi_kmer.rst) (beta-testing)
+* `Analyzing Genomes, Genome Assemblies, Metagenomic Contigs, or Proteomes` </docs/rgi_main.rst>`_ (a.k.a. RGI main)
+* `Analyzing Metagenomic Reads` </docs/rgi_bwt.rst>`_ (a.k.a. RGI bwt)
+* `K-mer Prediction of Pathogen-of-Origin for AMR Genes` </docs/rgi_kmer.rst>`_ (beta-testing)
 
 License
 --------

diff --git a/docs/rgi_kmer.rst b/docs/rgi_kmer.rst
@@ -16,7 +16,7 @@ As outlined above, CARD's `Resistomes & Variants <https://card.mcmaster.ca/genom
 
 CARD's k-mer classifiers assume the data submitted for analysis has been predicted to encode AMR genes, via RGI or another AMR bioinformatic tool. The k-mer data set was generated from and is intended exclusively for AMR sequence space. To be considered for a taxonomic prediction, individual sequences (e.g. FASTA, RGI predicted ORF, metagenomic read) must pass the *--minimum* coverage value (default of 10, i.e. the number of k-mers in a sequence that need to match a single category, for both taxonomic and genomic classifications, in order for a classification to be made for that sequence). Subsequent classification is based on the following logic tree:
 
-.. image:: images/kmerlogic.jpg
+.. image:: /images/kmerlogic.jpg
 
 .. code-block:: sh
 

diff --git a/docs/rgi_main.rst b/docs/rgi_main.rst
@@ -352,7 +352,7 @@ Generating Heat Maps of RGI main Results
 				                        Specify display options for categories (deafult=plain).
 				  --debug               debug mode
 
-.. image:: images/heatmap.jpg
+.. image:: /images/heatmap.jpg
 
 RGI heatmap produces EPS and PNG image files. An example where rows are organized by AMR Gene Family and columns clustered by similarity of resistome is shown above.