diff --git a/setup.cfg b/setup.cfg
index 096628c01..586fe9eae 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -73,8 +73,7 @@ bgen =
 fail_under = 100
 
 [tool:pytest]
-# TODO: remove ignored doctests below once Xarray>0.18.2 is released (with https://github.com/pydata/xarray/pull/4753)
-addopts = --doctest-modules --ignore=validation --cov-fail-under=100 --ignore=sgkit/stats/regenie.py --ignore=sgkit/stats/pca.py
+addopts = --doctest-modules --ignore=validation --cov-fail-under=100
 norecursedirs = .eggs build docs
 filterwarnings =
     error
diff --git a/sgkit/stats/pca.py b/sgkit/stats/pca.py
index eff18ecfb..91fe0aadb 100644
--- a/sgkit/stats/pca.py
+++ b/sgkit/stats/pca.py
@@ -257,8 +257,9 @@ def pca(
     ... )
     >>> ds.compute() # doctest: +NORMALIZE_WHITESPACE
     <xarray.Dataset>
-    Dimensions:                              (components: 2, samples: 150, variants: 100)
-    Dimensions without coordinates: components, samples, variants
+    Dimensions:                              (samples: 150, components: 2,
+                                              variants: 100)
+    Dimensions without coordinates: samples, components, variants
     Data variables:
         sample_pca_projection                (samples, components) float32 0.0103...
         sample_pca_component                 (variants, components) float32 0.096...
@@ -273,7 +274,7 @@ def pca(
     ...     .plot.scatter(x=("sample_pca_projection", 0), y=("sample_pca_projection", 1))
     ... )
     >>> ax
-    <AxesSubplot:xlabel='(sample_pca_projection, 0)', ylabel='(sample_pca_projection, 1)'>
+    <AxesSubplot: xlabel='(sample_pca_projection, 0)', ylabel='(sample_pca_projection, 1)'>
 
     References
     ----------
diff --git a/sgkit/stats/regenie.py b/sgkit/stats/regenie.py
index b76fd6672..ddab2a7ee 100644
--- a/sgkit/stats/regenie.py
+++ b/sgkit/stats/regenie.py
@@ -860,8 +860,9 @@ def regenie(
     >>> res = regenie(ds, dosage="call_dosage", covariates="sample_covariate", traits="sample_trait", merge=False)
     >>> res.compute() # doctest: +NORMALIZE_WHITESPACE
     <xarray.Dataset>
-    Dimensions:                  (alphas: 5, blocks: 2, contigs: 2, outcomes: 5, samples: 50)
-    Dimensions without coordinates: alphas, blocks, contigs, outcomes, samples
+    Dimensions:                  (blocks: 2, alphas: 5, samples: 50, outcomes: 5,
+                                  contigs: 2)
+    Dimensions without coordinates: blocks, alphas, samples, outcomes, contigs
     Data variables:
         regenie_base_prediction  (blocks, alphas, samples, outcomes) float64 0.33...
         regenie_meta_prediction  (samples, outcomes) float64 -0.4588 0.78 ... 0.3734