diff --git a/gnomad/utils/annotations.py b/gnomad/utils/annotations.py
index cc0c62306..416017fc0 100644
--- a/gnomad/utils/annotations.py
+++ b/gnomad/utils/annotations.py
@@ -334,6 +334,9 @@ def annotate_freq(
     pop_expr: Optional[hl.expr.StringExpression] = None,
     subpop_expr: Optional[hl.expr.StringExpression] = None,
     additional_strata_expr: Optional[Dict[str, hl.expr.StringExpression]] = None,
+    additional_strata_grouping_expr: Optional[
+        Dict[str, hl.expr.StringExpression]
+    ] = None,
     downsamplings: Optional[List[int]] = None,
 ) -> hl.MatrixTable:
     """
@@ -388,6 +391,7 @@ def annotate_freq(
     :param pop_expr: When specified, frequencies are stratified by population. If `sex_expr` is also specified, then a pop/sex stratifiction is added.
     :param subpop_expr: When specified, frequencies are stratified by sub-continental population. Note that `pop_expr` is required as well when using this option.
     :param additional_strata_expr: When specified, frequencies are stratified by the given additional strata found in the dict. This can e.g. be used to stratify by platform.
+    :param additional_strata_grouping_expr: When specified, frequencies are further stratified by groups within the additional_strata_expr. This can e.g. be used to stratify by platform-population.
     :param downsamplings: When specified, frequencies are computed by downsampling the data to the number of samples given in the list. Note that if `pop_expr` is specified, downsamplings by population is also computed.
     :return: MatrixTable with `freq` annotation
     """
@@ -396,10 +400,20 @@ def annotate_freq(
             "annotate_freq requires pop_expr when using subpop_expr"
         )
 
+    if additional_strata_grouping_expr is not None and additional_strata_expr is None:
+        raise NotImplementedError(
+            "annotate_freq requires additional_strata_expr when using"
+            " additional_strata_grouping_expr"
+        )
+
     if additional_strata_expr is None:
         additional_strata_expr = {}
 
     _freq_meta_expr = hl.struct(**additional_strata_expr)
+    if additional_strata_grouping_expr is None:
+        additional_strata_grouping_expr = {}
+    else:
+        _freq_meta_expr = _freq_meta_expr.annotate(**additional_strata_grouping_expr)
     if sex_expr is not None:
         _freq_meta_expr = _freq_meta_expr.annotate(sex=sex_expr)
     if pop_expr is not None:
@@ -410,7 +424,7 @@ def annotate_freq(
     # Annotate cols with provided cuts
     mt = mt.annotate_cols(_freq_meta=_freq_meta_expr)
 
-    # Get counters for sex, pop and subpop if set
+    # Get counters for sex, pop and if set subpop and additional strata
     cut_dict = {
         cut: hl.agg.filter(
             hl.is_defined(mt._freq_meta[cut]), hl.agg.counter(mt._freq_meta[cut])
@@ -509,6 +523,22 @@ def annotate_freq(
         + sample_group_filters
     )
 
+    # Add additional groupings to strata, e.g. strata-pop, strata-sex, strata-pop-sex
+    if additional_strata_grouping_expr is not None:
+        sample_group_filters.extend(
+            [
+                (
+                    {strata: str(s_value), add_strata: str(as_value)},
+                    (mt._freq_meta[strata] == s_value)
+                    & (mt._freq_meta[add_strata] == as_value),
+                )
+                for strata in additional_strata_expr
+                for s_value in cut_data.get(strata, {})
+                for add_strata in additional_strata_grouping_expr
+                for as_value in cut_data.get(add_strata, {})
+            ]
+        )
+
     freq_sample_count = mt.aggregate_cols(
         [hl.agg.count_where(x[1]) for x in sample_group_filters]
     )