diff --git a/.travis.yml b/.travis.yml
index 819d01d..0ad2d76 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -11,7 +11,6 @@ git:
   # https://github.com/travis-ci/travis-ci/issues/4575
   depth: 10
 cache:
-  pip: true
   # cache pip files; directory used for Ensembl downloads of GTF and FASTA files
   # along with the indexed db of intervals and ID mappings and pickles
   # of sequence dictionaries; vaxrank directory containing FM index of reference kmers
@@ -20,6 +19,7 @@ cache:
     - $HOME/.cache/pyensembl/GRCh38/ensembl87/
     - $HOME/.cache/pyensembl/GRCm38/ensembl87/
     - $HOME/.cache/vaxrank
+    - $HOME/.cache/pip
 before_install:
   - |
     if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then
diff --git a/vaxrank/__init__.py b/vaxrank/__init__.py
index 894cebc..fe7c60e 100644
--- a/vaxrank/__init__.py
+++ b/vaxrank/__init__.py
@@ -1 +1 @@
-__version__ = "0.7.8"
+__version__ = "0.7.9"
diff --git a/vaxrank/report.py b/vaxrank/report.py
index 56fefca..84203b4 100644
--- a/vaxrank/report.py
+++ b/vaxrank/report.py
@@ -116,14 +116,16 @@ def _patient_info(self):
         ])
         return patient_info
 
-    def _variant_data(self, top_vaccine_peptide):
+    def _variant_data(self, variant, top_vaccine_peptide):
         """
         Returns an OrderedDict with info used to populate variant info section.
         """
         variant_data = OrderedDict()
         mutant_protein_fragment = top_vaccine_peptide.mutant_protein_fragment
         top_score = _sanitize(top_vaccine_peptide.combined_score)
+        igv_locus = "chr%s:%d" % (variant.contig, variant.start)
         variant_data = OrderedDict([
+            ('IGV locus', igv_locus),
             ('Gene name', mutant_protein_fragment.gene_name),
             ('Top score', top_score),
             ('RNA reads supporting variant allele', mutant_protein_fragment.n_alt_reads),
@@ -300,7 +302,7 @@ def compute_template_data(self):
             num += 1
 
             top_peptide = vaccine_peptides[0]
-            variant_data = self._variant_data(top_peptide)
+            variant_data = self._variant_data(variant, top_peptide)
             predicted_effect = top_peptide.mutant_protein_fragment.predicted_effect()
             effect_data = self._effect_data(predicted_effect)