diff --git a/db/default_template.docx b/db/default_template.docx
index 5ad8b4c..272ea81 100644
Binary files a/db/default_template.docx and b/db/default_template.docx differ
diff --git a/db/tbdb.mask.bed b/db/tbdb.mask.bed
index d93b7fe..4f324f7 100644
--- a/db/tbdb.mask.bed
+++ b/db/tbdb.mask.bed
@@ -1,2292 +1,2292 @@
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-NC_000962.3	4411494	4411532
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+Chromosome	337461	337462
+Chromosome	337468	337525
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+Chromosome	337529	337571
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+Chromosome	337592	337593
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+Chromosome	350949	350952
+Chromosome	350953	350985
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+Chromosome	358250	358265
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+Chromosome	361717	361718
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+Chromosome	362122	362123
+Chromosome	362125	362126
+Chromosome	362145	362147
+Chromosome	362148	362149
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+Chromosome	426959	427034
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+Chromosome	2579850	2579855
+Chromosome	2579863	2579864
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+Chromosome	2610857	2610858
+Chromosome	2613882	2613884
+Chromosome	2613886	2613887
+Chromosome	2613890	2613933
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+Chromosome	2613936	2613938
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+Chromosome	2614424	2614426
+Chromosome	2614909	2614911
+Chromosome	2626015	2626022
+Chromosome	2626023	2626024
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+Chromosome	2626238	2626240
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+Chromosome	2632906	2632924
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+Chromosome	2636977	2636978
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+Chromosome	3795030	3795531
+Chromosome	3796034	3796430
+Chromosome	3797140	3797141
+Chromosome	3797818	3797819
+Chromosome	3797820	3797822
+Chromosome	3797827	3797834
+Chromosome	3799556	3799579
+Chromosome	3802090	3803599
+Chromosome	3803601	3803611
+Chromosome	3803612	3803613
+Chromosome	3803620	3803621
+Chromosome	3803719	3803721
+Chromosome	3803722	3803723
+Chromosome	3803724	3803739
+Chromosome	3803811	3803818
+Chromosome	3803822	3803823
+Chromosome	3803824	3803825
+Chromosome	3803826	3803827
+Chromosome	3803828	3803829
+Chromosome	3803854	3803898
+Chromosome	3803900	3803903
+Chromosome	3803905	3803907
+Chromosome	3841958	3841973
+Chromosome	3841974	3842400
+Chromosome	3842463	3842466
+Chromosome	3842469	3842500
+Chromosome	3842516	3842518
+Chromosome	3842532	3842571
+Chromosome	3843407	3843412
+Chromosome	3844667	3844669
+Chromosome	3844670	3844707
+Chromosome	3844756	3844761
+Chromosome	3846796	3847149
+Chromosome	3847150	3847152
+Chromosome	3847153	3847154
+Chromosome	3847656	3847754
+Chromosome	3847755	3847757
+Chromosome	3851874	3851889
+Chromosome	3851892	3851893
+Chromosome	3853489	3853500
+Chromosome	3853530	3853548
+Chromosome	3853708	3853709
+Chromosome	3858398	3858399
+Chromosome	3858401	3858402
+Chromosome	3858413	3858415
+Chromosome	3861877	3861969
+Chromosome	3862472	3862474
+Chromosome	3872901	3872906
+Chromosome	3874722	3874725
+Chromosome	3878542	3878665
+Chromosome	3878666	3878667
+Chromosome	3883663	3883664
+Chromosome	3883665	3883667
+Chromosome	3883668	3883672
+Chromosome	3883673	3883674
+Chromosome	3883677	3884058
+Chromosome	3884464	3884845
+Chromosome	3890749	3890750
+Chromosome	3890752	3890754
+Chromosome	3890755	3891161
+Chromosome	3891724	3892151
+Chromosome	3894616	3894638
+Chromosome	3895244	3895246
+Chromosome	3895306	3895309
+Chromosome	3895311	3895316
+Chromosome	3899726	3899811
+Chromosome	3902318	3902320
+Chromosome	3902818	3902830
+Chromosome	3902831	3902832
+Chromosome	3902836	3902839
+Chromosome	3909780	3909781
+Chromosome	3909785	3909786
+Chromosome	3909790	3909791
+Chromosome	3920174	3920175
+Chromosome	3920176	3920199
+Chromosome	3920200	3920218
+Chromosome	3927029	3927031
+Chromosome	3927038	3927048
+Chromosome	3927049	3927050
+Chromosome	3927051	3927053
+Chromosome	3927056	3927333
+Chromosome	3927341	3927342
+Chromosome	3927343	3927344
+Chromosome	3927351	3927363
+Chromosome	3927365	3927367
+Chromosome	3927368	3927370
+Chromosome	3927371	3927800
+Chromosome	3927804	3927814
+Chromosome	3927815	3927816
+Chromosome	3927818	3927819
+Chromosome	3927820	3927822
+Chromosome	3927931	3927941
+Chromosome	3927953	3927954
+Chromosome	3927958	3928537
+Chromosome	3928539	3928540
+Chromosome	3928599	3928647
+Chromosome	3928649	3928689
+Chromosome	3928690	3928694
+Chromosome	3928695	3928702
+Chromosome	3928703	3928704
+Chromosome	3928713	3928718
+Chromosome	3928719	3928723
+Chromosome	3928725	3928737
+Chromosome	3928760	3928761
+Chromosome	3928769	3928867
+Chromosome	3928905	3928906
+Chromosome	3928910	3928959
+Chromosome	3929050	3929051
+Chromosome	3929052	3929200
+Chromosome	3929203	3929204
+Chromosome	3929213	3929214
+Chromosome	3929219	3929236
+Chromosome	3929378	3929381
+Chromosome	3929392	3929413
+Chromosome	3929536	3929538
+Chromosome	3929539	3929540
+Chromosome	3929541	3929711
+Chromosome	3929715	3929716
+Chromosome	3929719	3929720
+Chromosome	3929739	3929828
+Chromosome	3929916	3929917
+Chromosome	3929949	3929965
+Chromosome	3929970	3929971
+Chromosome	3929972	3929987
+Chromosome	3929988	3929989
+Chromosome	3929991	3929992
+Chromosome	3930008	3930015
+Chromosome	3930020	3930073
+Chromosome	3930093	3930688
+Chromosome	3931126	3931130
+Chromosome	3931132	3931136
+Chromosome	3931140	3931141
+Chromosome	3931143	3932393
+Chromosome	3932395	3932411
+Chromosome	3932412	3933016
+Chromosome	3933017	3933018
+Chromosome	3933019	3933033
+Chromosome	3933035	3933060
+Chromosome	3933061	3933062
+Chromosome	3933064	3933066
+Chromosome	3933103	3933147
+Chromosome	3933229	3933233
+Chromosome	3933234	3933236
+Chromosome	3933237	3933256
+Chromosome	3933270	3933295
+Chromosome	3933296	3936630
+Chromosome	3936635	3936636
+Chromosome	3936638	3936639
+Chromosome	3936650	3936652
+Chromosome	3936661	3936673
+Chromosome	3936674	3936675
+Chromosome	3940107	3940466
+Chromosome	3940467	3940478
+Chromosome	3940480	3940498
+Chromosome	3940500	3940503
+Chromosome	3940504	3940506
+Chromosome	3940510	3940541
+Chromosome	3940543	3940546
+Chromosome	3940552	3940553
+Chromosome	3940577	3940578
+Chromosome	3940587	3940588
+Chromosome	3940593	3940595
+Chromosome	3940596	3940605
+Chromosome	3940606	3940608
+Chromosome	3940615	3940616
+Chromosome	3940617	3940619
+Chromosome	3940624	3940626
+Chromosome	3940628	3940629
+Chromosome	3940630	3940631
+Chromosome	3940634	3940635
+Chromosome	3940636	3940992
+Chromosome	3940995	3941010
+Chromosome	3941110	3941127
+Chromosome	3941199	3941215
+Chromosome	3941225	3941227
+Chromosome	3941231	3941232
+Chromosome	3941260	3941301
+Chromosome	3941306	3941308
+Chromosome	3941316	3942328
+Chromosome	3942336	3942337
+Chromosome	3942345	3942346
+Chromosome	3942348	3942349
+Chromosome	3942350	3942352
+Chromosome	3942369	3942370
+Chromosome	3942476	3942477
+Chromosome	3942478	3942549
+Chromosome	3942698	3944706
+Chromosome	3944707	3944708
+Chromosome	3944712	3944732
+Chromosome	3944736	3944737
+Chromosome	3944790	3944808
+Chromosome	3944809	3944810
+Chromosome	3944819	3944820
+Chromosome	3944821	3944822
+Chromosome	3944866	3944880
+Chromosome	3944881	3944882
+Chromosome	3945219	3945459
+Chromosome	3945915	3945916
+Chromosome	3945917	3945919
+Chromosome	3945921	3945929
+Chromosome	3945932	3948672
+Chromosome	3948673	3948675
+Chromosome	3948676	3948677
+Chromosome	3948686	3948687
+Chromosome	3948690	3948693
+Chromosome	3948721	3948722
+Chromosome	3948726	3948728
+Chromosome	3948732	3950070
+Chromosome	3950951	3951207
+Chromosome	3952919	3952937
+Chromosome	3954211	3954249
+Chromosome	3954262	3954264
+Chromosome	3971685	3971686
+Chromosome	3971693	3971696
+Chromosome	3971700	3971758
+Chromosome	3971759	3971762
+Chromosome	3972130	3972133
+Chromosome	3973911	3973912
+Chromosome	3973914	3973942
+Chromosome	3973943	3973944
+Chromosome	3987370	3987372
+Chromosome	3998059	3998071
+Chromosome	4010689	4010690
+Chromosome	4010692	4010780
+Chromosome	4030709	4030710
+Chromosome	4030711	4030712
+Chromosome	4030713	4030725
+Chromosome	4031672	4032763
+Chromosome	4032764	4032766
+Chromosome	4033034	4033035
+Chromosome	4033045	4033061
+Chromosome	4033074	4033075
+Chromosome	4036445	4036455
+Chromosome	4036465	4036467
+Chromosome	4036794	4037712
+Chromosome	4038846	4038864
+Chromosome	4038865	4038866
+Chromosome	4046657	4046658
+Chromosome	4046661	4046662
+Chromosome	4046663	4046668
+Chromosome	4046669	4046690
+Chromosome	4046819	4046820
+Chromosome	4053002	4053512
+Chromosome	4056958	4056959
+Chromosome	4058373	4058382
+Chromosome	4058391	4058394
+Chromosome	4058396	4058397
+Chromosome	4060108	4060391
+Chromosome	4061829	4061832
+Chromosome	4080057	4080059
+Chromosome	4080063	4080064
+Chromosome	4083331	4083332
+Chromosome	4083334	4083339
+Chromosome	4087542	4087551
+Chromosome	4092099	4092101
+Chromosome	4092909	4092912
+Chromosome	4093879	4093884
+Chromosome	4093972	4094382
+Chromosome	4101735	4101736
+Chromosome	4101742	4101743
+Chromosome	4101750	4101751
+Chromosome	4124313	4124342
+Chromosome	4124343	4124383
+Chromosome	4128335	4128411
+Chromosome	4130592	4130678
+Chromosome	4135452	4135453
+Chromosome	4135456	4135457
+Chromosome	4135459	4135462
+Chromosome	4135464	4135470
+Chromosome	4139531	4139532
+Chromosome	4139534	4139535
+Chromosome	4139536	4139537
+Chromosome	4139538	4139539
+Chromosome	4143727	4143728
+Chromosome	4149159	4149160
+Chromosome	4149161	4149221
+Chromosome	4155510	4155511
+Chromosome	4155525	4155529
+Chromosome	4156802	4156911
+Chromosome	4156915	4156926
+Chromosome	4175395	4175396
+Chromosome	4175397	4175414
+Chromosome	4176383	4176392
+Chromosome	4183891	4183895
+Chromosome	4189233	4189234
+Chromosome	4189235	4189236
+Chromosome	4189237	4189272
+Chromosome	4189961	4189967
+Chromosome	4190311	4190312
+Chromosome	4190314	4190347
+Chromosome	4190348	4190376
+Chromosome	4197138	4197140
+Chromosome	4198611	4198616
+Chromosome	4201199	4201310
+Chromosome	4212832	4212836
+Chromosome	4221070	4221072
+Chromosome	4222212	4222213
+Chromosome	4222214	4222309
+Chromosome	4222322	4222323
+Chromosome	4231228	4231230
+Chromosome	4231869	4231953
+Chromosome	4253015	4253367
+Chromosome	4253876	4254214
+Chromosome	4254215	4254217
+Chromosome	4274515	4274520
+Chromosome	4298230	4298231
+Chromosome	4303498	4303499
+Chromosome	4305063	4305066
+Chromosome	4310058	4310059
+Chromosome	4310060	4310242
+Chromosome	4318481	4318482
+Chromosome	4318483	4318811
+Chromosome	4318898	4319243
+Chromosome	4320135	4320151
+Chromosome	4320385	4320386
+Chromosome	4320388	4320391
+Chromosome	4320392	4320397
+Chromosome	4320399	4320400
+Chromosome	4320401	4320402
+Chromosome	4320406	4320408
+Chromosome	4320411	4320412
+Chromosome	4322039	4322041
+Chromosome	4328212	4328214
+Chromosome	4340881	4340883
+Chromosome	4340890	4341034
+Chromosome	4350748	4350754
+Chromosome	4353151	4353922
+Chromosome	4353923	4353924
+Chromosome	4358643	4358671
+Chromosome	4358687	4358688
+Chromosome	4358867	4358868
+Chromosome	4358869	4358871
+Chromosome	4358874	4359183
+Chromosome	4361006	4361136
+Chromosome	4368536	4368662
+Chromosome	4369462	4369709
+Chromosome	4370537	4370538
+Chromosome	4372452	4372453
+Chromosome	4375614	4375646
+Chromosome	4375660	4375661
+Chromosome	4375693	4375711
+Chromosome	4379044	4379049
+Chromosome	4383144	4383145
+Chromosome	4385743	4385744
+Chromosome	4400660	4400663
+Chromosome	4411494	4411532
diff --git a/db/tbdb.rules.txt b/db/tbdb.rules.txt
index ca49686..087889b 100644
--- a/db/tbdb.rules.txt
+++ b/db/tbdb.rules.txt
@@ -1,2 +1,2 @@
-Variant(gene_name=mmpL5,type=lof) inactivates_resistance Variant(gene_name=mmpR5)
-Variant(gene_name=eis,type=lof) inactivates_resistance Variant(gene_name=eis)
+Variant(gene_name=mmpL5,type=lof) inactivates_resistance Variant(gene_name=mmpR5) Loss of function variant found in mmpL5 which can abrogate the effect of genetically linked AwR and AwRI mmpR5 (Rv0678) resistance mutations.
+Variant(gene_name=eis,type=lof) inactivates_resistance Variant(gene_name=eis) Loss of function variant found in eis which can abrogate the effect of genetically linked AwR and AwRI eis resistance mutations.
diff --git a/tb-profiler b/tb-profiler
index 85de7cd..f59dce1 100644
--- a/tb-profiler
+++ b/tb-profiler
@@ -21,6 +21,7 @@ from rich.logging import RichHandler
 import importlib
 import pkgutil
 
+
 discovered_plugins = {
     name: importlib.import_module(name)
     for finder, name, ispkg
@@ -28,10 +29,7 @@ discovered_plugins = {
     if name.startswith('tbprofiler_')
 }
 
-docx_plugins = {
-    plugin.docx.__docx_template_name__:plugin for plugin in discovered_plugins.values()
-    if hasattr(plugin, 'docx')
-}
+
 
 
 __softwarename__ = 'tbprofiler'
@@ -115,11 +113,19 @@ def main_profile(args):
     tbp.process_tb_profiler_args(args)
 
     variants_profile = pp.run_profiler(args)
+
+    notes = set()
     if 'rules' in args.conf:
-        rules_applied = pp.apply_rules(args.conf['rules'], variants_profile)
+        rules_applied = pp.apply_rules(args.conf['rules'], variants_profile, just_make_note=True if args.implement_rules==False else False)
+        for var in variants_profile:
+            for ann in var.annotation:
+                if 'note' in ann:
+                    notes.add(ann['note'])
+
     else:
         rules_applied = []
 
+    logging.debug(rules_applied)
     tbp.clean_up_duplicate_annotations(variants_profile)
     # Convert variant objects to DrVariant if they cause resistance
     for var in variants_profile:
@@ -142,9 +148,6 @@ def main_profile(args):
     else:
         qc = pp.run_vcf_qc(args)
 
-    notes = []
-    for rule in rules_applied:
-        notes.append(f"Rule applied: {rule}")
 
     result = tbp.create_resistance_result(
         args = args,
@@ -192,6 +195,8 @@ def main_profile(args):
         "%s.bam.bai" % args.files_prefix: "%s/bam/%s.bam.bai" % (args.dir,args.prefix),
         "%s.nwk" % args.files_prefix: "%s/results/%s.nwk" % (args.dir,args.prefix),
     }
+    if args.save_low_dp_mask:
+        result_files["%s.%s.mask.bed" % (args.files_prefix,args.prefix)] = "%s/results/%s.mask.bed" % (args.dir,args.prefix)
     for file,target in result_files.items():
         if os.path.isfile(file):
             shutil.move(file,target)
@@ -350,6 +355,7 @@ def int_2_or_more(arg):
 
 
 variant_callers = [cls.__software__ for cls in vc.VariantCaller.__subclasses__()]
+docx_plugins = [cls.__template_name__ for cls in tbp.docx.DocxResultTemplate.__subclasses__()]
 
 
 
@@ -380,7 +386,7 @@ output.add_argument('--txt',action="store_true",help="Add text output")
 output.add_argument('--text_template','--text-template',type=str,help='Jinja2 formatted template for output')
 output.add_argument('--docx',action="store_true",help="Add docx output")
 output.add_argument('--docx_template','--docx-template',help="Supply custom template for --docx output")
-output.add_argument('--docx_plugin','--docx-plugin',choices=list(docx_plugins),help="Use a plugin template for --docx output")
+output.add_argument('--docx_plugin','--docx-plugin',choices=docx_plugins,help="Use a plugin template for --docx output")
 output.add_argument('--add_columns','--add-columns',default=None,type=str,help="Add additional columns found in the mutation database to the text and csv results")
 output.add_argument('--add_mutation_metadata','--add-mutation-metadata',action="store_true",help=argparse.SUPPRESS)
 output.add_argument('--dir','-d',default=".",help='Storage directory')
@@ -420,12 +426,15 @@ algorithm.add_argument('--no_lineage','--no-lineage',action="store_true",help=ar
 algorithm.add_argument('--add_variant_annotations','--add-variant-annotations',action="store_true",help=argparse.SUPPRESS)
 algorithm.add_argument('--threads','-t',default=1,help='Threads to use',type=int)
 algorithm.add_argument('--ram',default=2,help='Maximum memory to use',type=int)
+algorithm.add_argument('--implement_rules','--implement-rules',action="store_true",help='Use rules implemented in the resistance library (by default only a note will be made)')
 
 other=parser_sub.add_argument_group("Other options")
 other.add_argument('--logging',type=str.upper,default="INFO",choices=["DEBUG","INFO","WARNING","ERROR","CRITICAL"],help='Logging level')
 other.add_argument('--debug',action='store_true',help=argparse.SUPPRESS)
 other.add_argument('--delly_vcf','--delly-vcf',help=argparse.SUPPRESS)
 other.add_argument('--supplementary_bam','--supplementary-bam',help=argparse.SUPPRESS)
+other.add_argument('--low_dp_mask','--low-dp-mask',help=argparse.SUPPRESS)
+other.add_argument('--save_low_dp_mask','--save-low-dp-mask',action='store_true',help=argparse.SUPPRESS)
 other.add_argument('--no_clean','--no-clean', action='store_true',help=argparse.SUPPRESS)
 other.add_argument('--temp',help="Temp firectory to process all files",type=str,default=".")
 other.add_argument('--version', action='version', version="tb-profiler version %s" % tbp.__version__)
diff --git a/tbprofiler/__init__.py b/tbprofiler/__init__.py
index 5441640..f966fdd 100644
--- a/tbprofiler/__init__.py
+++ b/tbprofiler/__init__.py
@@ -6,5 +6,6 @@
 from .output import *
 from .snp_dists import *
 from .phylo import *
+from .docx import *
 
-__version__ = "6.3.0"
+__version__ = "6.4.0"
diff --git a/tbprofiler/docx.py b/tbprofiler/docx.py
index fb4dc5e..2911d27 100644
--- a/tbprofiler/docx.py
+++ b/tbprofiler/docx.py
@@ -1,11 +1,22 @@
 import sys
 from docxtpl import DocxTemplate
 from collections import defaultdict
-from .models import ProfileResult
+from .models import ProfileResult, VcfQC
 from docx import Document
 from typing import List
 from copy import deepcopy
 import logging
+from abc import abstractmethod
+from .utils import rv2genes, get_gene2drugs
+import os
+
+
+
+class DocxResultTemplate:
+    @abstractmethod
+    def write_output(self, result: ProfileResult, conf: dict, outfile: str):
+        """Write the output to the Word document"""
+        pass
 
 def sanitize(d):
     d = d.replace("-","_")
@@ -33,11 +44,16 @@ def _merge_cells(tab, rows: List[int], column: int):
             return 
         c1 = tab.cell(rows[0], column)
         c2 = tab.cell(rows[-1], column)
-        
+        c1_font_size = c1.paragraphs[0].runs[0].font.size
+
         for r in rows[1:]:
-            tab.cell(r, column).text = ""
+            tab.cell(r, column).text = ''
+     
+
         cm = c1.merge(c2)
 
+
+            
         values_in_next_column = set([tab.rows[r].cells[column+1].text for r in rows])
         for val in values_in_next_column:
             rows_with_val = [r for r in rows if tab.c[r][column+1].text == val]
@@ -54,90 +70,261 @@ def _merge_cells(tab, rows: List[int], column: int):
     doc.save(filename)
 
 
+class DefaultTemplate(DocxResultTemplate):
+    __template_name__ = "default"
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        __dir__ = os.path.dirname(os.path.abspath(__file__))
+        # self.template_filename = f"{__dir__}/template.docx"
+        self.template_filename = sys.prefix+"/share/tbprofiler/default_template.docx"
+    def write_output(
+            self, 
+            result: ProfileResult, 
+            conf: dict,
+            output_filename: str):
+        
+        id2name = rv2genes(conf['bed'])
+        db = conf['json_db']
+        tier1_genes = set()
+        for gene in db:
+            for var in db[gene]:
+                for ann in db[gene][var]['annotations']:
+                    if ann['type']=='drug_resistance':
+                        tier1_genes.add(id2name[gene])
+        
+        tier1_genes.add('mmpL5')
+
+        if isinstance(result.qc, VcfQC):
+            qc_check = {d:100 for d in id2name.values()}
+            result.notes.append("This report was generated from a VCF where gene coverage is not available. It is assumed all genes are covered well sufficiently.")
+        else:
+            qc_check = {d.target:d.percent_depth_pass for d in result.qc.target_qc}
+
+
+        gene2drugs = get_gene2drugs(conf['bed'])
+        table = [{'name':d, 'genes':[]} for d in conf['drugs']]
+        for gene,drugs in gene2drugs.items():
+            if gene not in tier1_genes: continue
+            for d in drugs:
+                item = [i for i in table if i['name']==d][0]
+                item['genes'].append({'name':gene, 'variants':[]})
+
+        for var in result.dr_variants:
+            for d in var.drugs:
+                item = [i for i in table if i['name']==d['drug']][0]
+                gene_item = [i for i in item['genes'] if i['name']==var.gene_name][0]
+                gene_item['variants'].append({
+                    'change':var.change,
+                    'freq':var.freq,
+                    'confidence':d['confidence'],
+                    'comment':d['comment']
+                })
+
+        comments = {}
+        rows = []
+        for d in table:
+            for g in d['genes']:
+                if len(g['variants']) == 0:
+                    rows.append({
+                        'drug':d['name'].replace("_"," ").title(),
+                        'gene':g['name'],
+                        'qc':qc_check[g['name']],
+                        'change':'',
+                        'freq':'',
+                        'confidence':'',
+                        'comment':''
+                    })
+                else:
+                    for v in g['variants']:
+                        if v['comment']!="" and v['comment'] not in comments:
+                            comments[v['comment']] = len(comments) + 1
+                        rows.append({
+                            'drug':d['name'].replace("_"," ").title(),
+                            'gene':g['name'],
+                            'qc':qc_check[g['name']],
+                            'change':v['change'],
+                            'freq':int(v['freq']*100),
+                            'confidence':v['confidence'] if v['confidence']!="" else "Uncertain significance",
+                            'comment':comments.get(v['comment'],'')
+                        })
+
+        resistant_drugs_tmp = [r['drug'] for r in rows if r['change']!=""]
+        resistant_drugs = [d for d in conf['drugs'] if d.title() in resistant_drugs_tmp]
+        if len(resistant_drugs)>0:
+            result_summary = f"Known resistance variants for {', '.join(resistant_drugs[:-1])} and {resistant_drugs[-1]} detected."
+        else:
+            result_summary = "No known resistance variants detected."
+
+
+        poor_coverage_genes = [g for g in qc_check if qc_check[g]<99]
+        if len(poor_coverage_genes)>0:
+            result.notes.append(f"Insufficient coverage detected in {len(poor_coverage_genes)} genes.")
+
+        fail_variants = []
+        fail_comments = {}
+        for var in result.qc_fail_variants:
+            if not hasattr(var,'drugs'): continue
+            for d in var.drugs:
+
+                if d['comment']!="" and d['comment'] not in fail_comments:
+                    fail_comments[d['comment']] = len(fail_comments) + 1
+                fail_variants.append({
+                    'drug':d['drug'],
+                    'gene':var.gene_name,
+                    'qc':qc_check[var.gene_name],
+                    'change':var.change,
+                    'confidence':d['confidence'],
+                    'freq':int(var.freq*100),
+                    'depth':var.depth,
+                    'comment':fail_comments.get(d['comment'],'')
+                })
+            if var.gene_name in ('mmpL5','mmpS5') and var.type=='frameshift_variant':
+                for ann in var.annotation:
+                    if ann['type']=='who_confidence' and ann['original_mutation']=='LoF':
+                        fail_variants.append({
+                            'drug':ann['drug'],
+                            'gene':var.gene_name,
+                            'qc':qc_check[var.gene_name],
+                            'change':var.change,
+                            'confidence':ann['confidence'],
+                            'freq':int(var.freq*100),
+                            'depth':var.depth,
+                            'comment':fail_comments.get(ann['comment'],'')
+                        })
+                        
+        fail_variants_unique = set([(f['gene'],f['change']) for f in fail_variants])
+        if len(fail_variants)>0:
+            result.notes.append(f"{len(fail_variants_unique)} resistance variants failed QC checks. These have not been used to generate the mutation report. See QC failed variants table for details.")
+
+
+        other_variants = []
+        other_comments = {}
+        for var in result.other_variants:
+            drug_annotation = {a['drug']:a for a in var.annotation if a['type']=='who_confidence'}
+            for drug_name in var.gene_associated_drugs:
+                d = drug_annotation.get(drug_name,{})
+                if d.get('comment','')!='' and d['comment'] not in other_comments:
+                    other_comments[d['comment']] = len(other_comments) + 1
+                other_variants.append({
+                    'drug':drug_name,
+                    'gene':var.gene_name,
+                    'qc':qc_check[var.gene_name],
+                    'change':var.change,
+                    'confidence':d.get('confidence','Uncertain significance'),
+                    'freq':int(var.freq*100),
+                    'depth':var.depth,
+                    'comment':other_comments.get(d.get('comment',''),'')
+                })
+
+
+
+        context = {
+            'd': result.model_dump(),
+            'result_summary': result_summary,
+            'rows':rows,
+            'comments': comments,
+            'qc_check': qc_check,
+            'notes': ' '.join(result.notes),
+            'fail_variants': fail_variants,
+            'fail_comments': fail_comments,
+            'other_variants': other_variants,
+            'other_comments': other_comments
+        }
+
+        tpl = DocxTemplate(self.template_filename)
+        tpl.render(context)
+        tpl.save(output_filename)
+
+        merge_cells(output_filename)
+
+
 
 def write_docx(result: ProfileResult,conf,outfile,template_file = None, plugin = None):
     if template_file is None:
         template_file = sys.prefix+"/share/tbprofiler/default_template.docx"
     
     if plugin:
-        variables = plugin.docx.create_output(result, conf)
+        plugin_cls = plugin()
+        plugin_cls.write_output(result, conf,outfile)
 
     else:
 
-        dr_variant_table = []
-        comments = []
+        output_cls = DefaultTemplate()
+        output_cls.write_output(result, conf, outfile)
+        # dr_variant_table = []
+        # comments = []
         
-        for var in result.dr_variants:
-            for drug in var.drugs:
-                mutation = var.change if len(var.change) < 15 else var.change[:11]+"..."+var.change[-3:]
-                if drug['comment'] not in comments and len(drug['comment']):
-                    comments.append(drug['comment'])
-                dr_variant_table.append({
-                    'drug': drug['drug'],
-                    'gene': var.gene_name,
-                    'mutation': mutation,
-                    'depth': var.depth,
-                    'frequency': round(var.freq * 100,2),
-                    'confidence': drug['confidence'],
-                    'comment': comments.index(drug['comment'])+1 if len(drug['comment']) else ""
-                })
-        drugs_found = set([x['drug'] for x in dr_variant_table])
-        for drug in conf['drugs']:
-            if drug not in drugs_found:
-                dr_variant_table.append({
-                    'drug': drug,
-                    'gene': "",
-                    'mutation': "",
-                    'depth': "",
-                    'frequency': "",
-                    'confidence': "",
-                    'comment': ""
-                })
+        # for var in result.dr_variants:
+        #     for drug in var.drugs:
+        #         mutation = var.change if len(var.change) < 15 else var.change[:11]+"..."+var.change[-3:]
+        #         if drug['comment'] not in comments and len(drug['comment']):
+        #             comments.append(drug['comment'])
+        #         dr_variant_table.append({
+        #             'drug': drug['drug'],
+        #             'gene': var.gene_name,
+        #             'mutation': mutation,
+        #             'depth': var.depth,
+        #             'frequency': round(var.freq * 100,2),
+        #             'confidence': drug['confidence'],
+        #             'comment': comments.index(drug['comment'])+1 if len(drug['comment']) else ""
+        #         })
+        # drugs_found = set([x['drug'] for x in dr_variant_table])
+        # for drug in conf['drugs']:
+        #     if drug not in drugs_found:
+        #         dr_variant_table.append({
+        #             'drug': drug,
+        #             'gene': "",
+        #             'mutation': "",
+        #             'depth': "",
+        #             'frequency': "",
+        #             'confidence': "",
+        #             'comment': ""
+        #         })
 
-        gene_qc = []
-        if 'target_qc' in result.qc:
-            for item in result.qc.target_qc:
+        # gene_qc = []
+        # if 'target_qc' in result.qc:
+        #     for item in result.qc.target_qc:
 
-                gene_qc.append({
-                    'status': 'ok' if item.percent_depth_pass>0.9 else 'fail',
-                    'gene': item.target,
-                    'median_depth': item.median_depth,
-                    'percent_depth_pass': item.percent_depth_pass,
-                })
+        #         gene_qc.append({
+        #             'status': 'ok' if item.percent_depth_pass>0.9 else 'fail',
+        #             'gene': item.target,
+        #             'median_depth': item.median_depth,
+        #             'percent_depth_pass': item.percent_depth_pass,
+        #         })
 
-        dr_variant_table = sorted(dr_variant_table,key=lambda x: conf['drugs'].index(x['drug']))
+        # dr_variant_table = sorted(dr_variant_table,key=lambda x: conf['drugs'].index(x['drug']))
 
-        other_variants_table = []
-        for var in result.other_variants:
-            for ann in var.annotation:
-                other_variants_table.append({
-                    'gene': var.gene_name,
-                    'mutation': var.change,
-                    'depth': var.depth,
-                    'frequency': round(var.freq * 100,2),
-                    'drug': ann['drug'],
-                    'confidence': ann['confidence'],
-                })
+        # other_variants_table = []
+        # for var in result.other_variants:
+        #     for ann in var.annotation:
+        #         other_variants_table.append({
+        #             'gene': var.gene_name,
+        #             'mutation': var.change,
+        #             'depth': var.depth,
+        #             'frequency': round(var.freq * 100,2),
+        #             'drug': ann['drug'],
+        #             'confidence': ann['confidence'],
+        #         })
         
-        data = result.model_dump()
+        # data = result.model_dump()
 
 
 
-        variables = {
-            'date':data['timestamp'].strftime("%d %b %Y"),
-            'sublineage': data['sub_lineage'],
-            'version': data['pipeline']['software_version'],
-            'drtype': data['drtype'],
-            'd': data,
-            'dr_variants_table': dr_variant_table,
-            'other_variants_table': other_variants_table,
-            'comments': comments,
-            'gene_qc': gene_qc
-        }
+        # variables = {
+        #     'date':data['timestamp'].strftime("%d %b %Y"),
+        #     'sublineage': data['sub_lineage'],
+        #     'version': data['pipeline']['software_version'],
+        #     'drtype': data['drtype'],
+        #     'd': data,
+        #     'dr_variants_table': dr_variant_table,
+        #     'other_variants_table': other_variants_table,
+        #     'comments': comments,
+        #     'gene_qc': gene_qc
+        # }
 
 
-        doc = DocxTemplate(template_file)
-        doc.render(variables)
-        doc.save(outfile)
+        # doc = DocxTemplate(template_file)
+        # doc.render(variables)
+        # doc.save(outfile)
 
-        merge_cells(outfile)
\ No newline at end of file
+        # merge_cells(outfile)
\ No newline at end of file
diff --git a/tbprofiler/output.py b/tbprofiler/output.py
index 317df59..6e880b8 100644
--- a/tbprofiler/output.py
+++ b/tbprofiler/output.py
@@ -1,7 +1,8 @@
 from .text import write_text
-from .docx import write_docx
+from .docx import write_docx, DocxResultTemplate
 import logging
 from .models import ProfileResult
+from pathogenprofiler import FastaQC, BamQC, VcfQC
 
 def write_outputs(args,result: ProfileResult,template_file: str = None):
     logging.info("Writing outputs")
@@ -23,5 +24,7 @@ def write_outputs(args,result: ProfileResult,template_file: str = None):
     if args.docx:
         logging.info(f"Writing docx file: {docx_output}")
         if args.docx_plugin:
-            args.docx_plugin = args.plugins[args.docx_plugin]
-        write_docx(result,args.conf,docx_output,template_file = args.docx_template, plugin = args.docx_plugin)
\ No newline at end of file
+            available_plugins = {cls.__template_name__:cls for cls in DocxResultTemplate.__subclasses__()}
+            args.docx_plugin = available_plugins[args.docx_plugin]
+
+        write_docx(result,args.conf,docx_output,template_file = args.docx_template, plugin = args.docx_plugin)
diff --git a/tbprofiler/phylo.py b/tbprofiler/phylo.py
index 7fe855f..ace02d7 100644
--- a/tbprofiler/phylo.py
+++ b/tbprofiler/phylo.py
@@ -83,7 +83,7 @@ def prepare_usher(treefile: str,vcf_file: str) -> None:
 def prepare_sample_consensus(sample: str,input_vcf: str,args: argparse.Namespace) -> str:
     s = sample
     tmp_vcf = f"{args.files_prefix}.{s}.vcf.gz"
-    run_cmd(f"bcftools norm -m - {input_vcf} | bcftools view -T ^{args.conf['bedmask']} | bcftools filter --SnpGap 50 | bcftools view -v snps | annotate_maaf.py | bcftools filter -S . -e 'MAAF<0.7' |bcftools filter -S . -e 'FMT/DP<{args.conf['variant_filters']['depth_soft']}' | rename_vcf_sample.py --sample-name {s} | bcftools view -v snps -Oz -o {tmp_vcf}")
+    run_cmd(f"bcftools norm -m - {input_vcf} | bcftools view -T ^{args.conf['bedmask']} | bcftools view -v snps | annotate_maaf.py | bcftools filter -S . -e 'MAAF<0.7' |bcftools filter -S . -e 'FMT/DP<{args.conf['variant_filters']['depth_soft']}' | bcftools filter --SnpGap 50 |rename_vcf_sample.py --sample-name {s} | bcftools view -v snps -Oz -o {tmp_vcf}")
     run_cmd(f"bcftools index {tmp_vcf}")
 
     mask_bed = f"{args.files_prefix}.{s}.mask.bed"
@@ -92,6 +92,9 @@ def prepare_sample_consensus(sample: str,input_vcf: str,args: argparse.Namespace
     if args.bam:
         generate_low_dp_mask(f"{args.bam}",args.conf['ref'],mask_bed)
         mask_cmd = f"-m {mask_bed} -M N"
+    elif args.low_dp_mask:
+        mask_bed = args.low_dp_mask
+        mask_cmd = f"-m {mask_bed} -M N"
     elif args.vcf:
         generate_low_dp_mask_vcf(args.vcf,mask_bed)
         mask_cmd = f"-m {mask_bed} -M N"
diff --git a/tbprofiler/reformat.py b/tbprofiler/reformat.py
index 02da7ba..9d78422 100644
--- a/tbprofiler/reformat.py
+++ b/tbprofiler/reformat.py
@@ -270,7 +270,7 @@ def clean_up_duplicate_annotations(variants: Variant) -> None:
     """
     confidence_levels = ['Assoc w R','Assoc w R - Interim','Uncertain significance','Not assoc w R - Interim','Not assoc w R']
     for var in variants:
-        keys = set([(ann['type'],ann['drug']) for ann in var.annotation])
+        keys = sorted(list(set([(ann['type'],ann['drug']) for ann in var.annotation])))
         new_annotations = []
         for key in keys:
             confidence_anns = []