diff --git a/CHANGES b/CHANGES
index ae3f3068a2..78e739c567 100644
--- a/CHANGES
+++ b/CHANGES
@@ -1,6 +1,7 @@
 Next release
 ============
 
+* ENH: Add new flags to the BRAINSABC for new featues (https://github.com/nipy/nipype/pull/1322)
 * ENH: Provides a Nipype wrapper for ANTs DenoiseImage (https://github.com/nipy/nipype/pull/1291)
 * FIX: Minor bugfix logging hash differences (https://github.com/nipy/nipype/pull/1298)
 * FIX: Use released Prov python library (https://github.com/nipy/nipype/pull/1279)
diff --git a/nipype/algorithms/tests/test_auto_ErrorMap.py b/nipype/algorithms/tests/test_auto_ErrorMap.py
new file mode 100644
index 0000000000..69484529dd
--- /dev/null
+++ b/nipype/algorithms/tests/test_auto_ErrorMap.py
@@ -0,0 +1,35 @@
+# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
+from ...testing import assert_equal
+from ..metrics import ErrorMap
+
+
+def test_ErrorMap_inputs():
+    input_map = dict(ignore_exception=dict(nohash=True,
+    usedefault=True,
+    ),
+    in_ref=dict(mandatory=True,
+    ),
+    in_tst=dict(mandatory=True,
+    ),
+    mask=dict(),
+    metric=dict(mandatory=True,
+    usedefault=True,
+    ),
+    out_map=dict(),
+    )
+    inputs = ErrorMap.input_spec()
+
+    for key, metadata in list(input_map.items()):
+        for metakey, value in list(metadata.items()):
+            yield assert_equal, getattr(inputs.traits()[key], metakey), value
+
+
+def test_ErrorMap_outputs():
+    output_map = dict(distance=dict(),
+    out_map=dict(),
+    )
+    outputs = ErrorMap.output_spec()
+
+    for key, metadata in list(output_map.items()):
+        for metakey, value in list(metadata.items()):
+            yield assert_equal, getattr(outputs.traits()[key], metakey), value
diff --git a/nipype/algorithms/tests/test_auto_Overlap.py b/nipype/algorithms/tests/test_auto_Overlap.py
new file mode 100644
index 0000000000..a5a3874bd1
--- /dev/null
+++ b/nipype/algorithms/tests/test_auto_Overlap.py
@@ -0,0 +1,47 @@
+# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
+from ...testing import assert_equal
+from ..misc import Overlap
+
+
+def test_Overlap_inputs():
+    input_map = dict(bg_overlap=dict(mandatory=True,
+    usedefault=True,
+    ),
+    ignore_exception=dict(nohash=True,
+    usedefault=True,
+    ),
+    mask_volume=dict(),
+    out_file=dict(usedefault=True,
+    ),
+    vol_units=dict(mandatory=True,
+    usedefault=True,
+    ),
+    volume1=dict(mandatory=True,
+    ),
+    volume2=dict(mandatory=True,
+    ),
+    weighting=dict(usedefault=True,
+    ),
+    )
+    inputs = Overlap.input_spec()
+
+    for key, metadata in list(input_map.items()):
+        for metakey, value in list(metadata.items()):
+            yield assert_equal, getattr(inputs.traits()[key], metakey), value
+
+
+def test_Overlap_outputs():
+    output_map = dict(dice=dict(),
+    diff_file=dict(),
+    jaccard=dict(),
+    labels=dict(),
+    roi_di=dict(),
+    roi_ji=dict(),
+    roi_voldiff=dict(),
+    volume_difference=dict(),
+    )
+    outputs = Overlap.output_spec()
+
+    for key, metadata in list(output_map.items()):
+        for metakey, value in list(metadata.items()):
+            yield assert_equal, getattr(outputs.traits()[key], metakey), value
diff --git a/nipype/interfaces/semtools/segmentation/specialized.py b/nipype/interfaces/semtools/segmentation/specialized.py
index 2454cd3c18..ec2395a200 100644
--- a/nipype/interfaces/semtools/segmentation/specialized.py
+++ b/nipype/interfaces/semtools/segmentation/specialized.py
@@ -319,6 +319,8 @@ class BRAINSABCInputSpec(CommandLineInputSpec):
     filterMethod = traits.Enum("None", "CurvatureFlow", "GradientAnisotropicDiffusion", "Median", desc="Filter method for preprocessing of registration", argstr="--filterMethod %s")
     maxBiasDegree = traits.Int(desc="Maximum bias degree", argstr="--maxBiasDegree %d")
     useKNN = traits.Bool(desc="Use the KNN stage of estimating posteriors.", argstr="--useKNN ")
+    purePlugsThreshold = traits.Float(desc="If this threshold value is greater than zero, only pure samples are used to compute the distributions in EM classification, and only pure samples are used for KNN training. The default value is set to 0, that means not using pure plugs. However, a value of 0.2 is suggested if you want to activate using pure plugs option.", argstr="--purePlugsThreshold %f")
+    numberOfSubSamplesInEachPlugArea = InputMultiPath(traits.Int, desc="Number of continous index samples taken at each direction of lattice space for each plug volume.", sep=",", argstr="--numberOfSubSamplesInEachPlugArea %s")
     atlasWarpingOff = traits.Bool(desc="Deformable registration of atlas to subject", argstr="--atlasWarpingOff ")
     gridSize = InputMultiPath(traits.Int, desc="Grid size for atlas warping with BSplines", sep=",", argstr="--gridSize %s")
     defaultSuffix = traits.Str(argstr="--defaultSuffix %s")
diff --git a/nipype/interfaces/semtools/segmentation/tests/test_auto_BRAINSABC.py b/nipype/interfaces/semtools/segmentation/tests/test_auto_BRAINSABC.py
index 2d0ea9442f..871e5df311 100644
--- a/nipype/interfaces/semtools/segmentation/tests/test_auto_BRAINSABC.py
+++ b/nipype/interfaces/semtools/segmentation/tests/test_auto_BRAINSABC.py
@@ -54,6 +54,9 @@ def test_BRAINSABC_inputs():
     medianFilterSize=dict(argstr='--medianFilterSize %s',
     sep=',',
     ),
+    numberOfSubSamplesInEachPlugArea=dict(argstr='--numberOfSubSamplesInEachPlugArea %s',
+    sep=',',
+    ),
     numberOfThreads=dict(argstr='--numberOfThreads %d',
     ),
     outputDir=dict(argstr='--outputDir %s',
@@ -72,6 +75,8 @@ def test_BRAINSABC_inputs():
     ),
     posteriorTemplate=dict(argstr='--posteriorTemplate %s',
     ),
+    purePlugsThreshold=dict(argstr='--purePlugsThreshold %f',
+    ),
     restoreState=dict(argstr='--restoreState %s',
     ),
     saveState=dict(argstr='--saveState %s',