diff --git a/cloudbuild_CI.yaml b/cloudbuild_CI.yaml
index 81f2cbb10..5ec4559f8 100644
--- a/cloudbuild_CI.yaml
+++ b/cloudbuild_CI.yaml
@@ -42,7 +42,9 @@ steps:
       - '--project ${PROJECT_ID}'
       - '--image_tag ${COMMIT_SHA}'
       - '--run_unit_tests'
-      - '--run_presubmit_tests'
+      - '--run_preprocessor_tests'
+      - '--run_bq_to_vcf_tests'
+      - '--run_all_tests'
       - '--test_name_prefix cloud-ci-'
     id: 'test-gcp-variant-transforms-docker'
     entrypoint: '/opt/gcp_variant_transforms/src/deploy_and_run_tests.sh'
diff --git a/gcp_variant_transforms/libs/bigquery_util.py b/gcp_variant_transforms/libs/bigquery_util.py
index eb3256799..0b7f54120 100644
--- a/gcp_variant_transforms/libs/bigquery_util.py
+++ b/gcp_variant_transforms/libs/bigquery_util.py
@@ -57,7 +57,7 @@
 _BQ_EXTRACT_SCHEMA_COMMAND = (
     'bq show --schema --format=prettyjson {FULL_TABLE_ID} > {SCHEMA_FILE_PATH}')
 _GCS_DELETE_FILES_COMMAND = 'gsutil -m rm -f -R {ROOT_PATH}'
-_BQ_NUM_RETRIES = 3
+_BQ_NUM_RETRIES = 5
 _MAX_NUM_CONCURRENT_BQ_LOAD_JOBS = 4
 
 _GET_COLUMN_NAMES_QUERY = (
@@ -502,7 +502,21 @@ def create_sample_info_table(output_table_id):
   _run_table_creation_command(bq_command)
 
 class FlattenCallColumn(object):
+  """Flattens call column to convert varinat opt tables to sample opt tables."""
+
   def __init__(self, base_table_id, suffixes):
+    # type (str, List[str]) -> None
+    """Initialize `FlattenCallColumn` object.
+
+    In preparation to convert variant lookup optimized tables to sample lookup
+    optimized tables, we initiate this class with the base table name of variant
+    opt table (set using --output_table flag) and the list of suffixes (which
+    are extracted from sharding config file).
+
+    Args:
+      base_table_id: Base name of variant opt outputs (set by --output_table).
+      suffixes: List of suffixes (extracted from sharding config file).
+    """
     (self._project_id,
      self._dataset_id,
      self._base_table) = parse_table_reference(base_table_id)
@@ -589,7 +603,7 @@ def _copy_to_flatten_table(self, output_table_id, cp_query):
         break
     logging.info('Copy to table query was successful: %s', output_table_id)
 
-  def _create_temp_flatten_table(self):
+  def _create_temp_flatten_table_with_1_row(self):
     temp_suffix = time.strftime('%Y%m%d_%H%M%S')
     temp_table_id = '{}{}'.format(self._schema_table_id, temp_suffix)
     full_output_table_id = '{}.{}.{}'.format(
@@ -610,7 +624,21 @@ def _create_temp_flatten_table(self):
     return temp_table_id
 
   def get_flatten_table_schema(self, schema_file_path):
-    temp_table_id = self._create_temp_flatten_table()
+    # type: (str) -> bool
+    """Write the flatten table's schema to the given json file.
+
+    This method basically performs the following tasks:
+      * composes a 'flattening query' based on _schema_table_id table's schema.
+      * Runs the 'flattening query' to read 1 row and writes it to a temp table.
+      * Extracts the schema of the temp table using _BQ_EXTRACT_SCHEMA_COMMAND.
+
+    Args:
+      schema_file_path: The json schema will be written to this file.
+
+    Returns;
+      A bool value indicating if the schema was successfully extracted.
+    """
+    temp_table_id = self._create_temp_flatten_table_with_1_row()
     full_table_id = '{}:{}.{}'.format(
         self._project_id, self._dataset_id, temp_table_id)
     bq_command = _BQ_EXTRACT_SCHEMA_COMMAND.format(
@@ -626,9 +654,22 @@ def get_flatten_table_schema(self, schema_file_path):
       logging.info('Successfully deleted temporary table: %s', full_table_id)
     else:
       logging.error('Was not able to delete temporary table: %s', full_table_id)
-    return result
+    return result == 0
 
   def copy_to_flatten_table(self, output_base_table_id):
+    # type: (str) -> None
+    """Copies data from variant lookup optimized tables to sample lookup tables.
+
+    Copies rows from _base_table_id__* to output_base_table_id__* for each value
+    of _suffixes. Here we assume destination tables are already created and are
+    partitioned based on call_sample_id column. The copying process is done via
+    a flattening query so if the source tables have repeated sample_ids the
+    output table will have more rows. In fact:
+    # of output rows = # of input rows * # of sample_ids
+
+    Args:
+      output_base_table_id: Base table name of output tables.
+    """
     # Here we assume all output_table_base + suffices[:] are already created.
     (output_project_id,
      output_dataset_id,
diff --git a/gcp_variant_transforms/options/variant_transform_options.py b/gcp_variant_transforms/options/variant_transform_options.py
index e0c8c495d..b60929e71 100644
--- a/gcp_variant_transforms/options/variant_transform_options.py
+++ b/gcp_variant_transforms/options/variant_transform_options.py
@@ -141,10 +141,14 @@ def add_arguments(self, parser):
         '--sample_lookup_optimized_output_table',
         default='',
         help=('In addition to the default output tables (which are optimized '
-              'for variant look up queries), you can store a second copy of '
+              'for variant lookup queries), you can store a second copy of '
               'your data in BigQuery tables that are optimized for sample '
-              'look up queries. Note that setting this option will double your '
-              'BigQuery storage costs.'))
+              'lookup queries using this flag.'
+              'Note that setting this flag will *at least* double your '
+              'BigQuery storage costs. If your input VCF files are joint '
+              'genotyped (say with n sample) then sample lookup tables will '
+              'have n * the number of rows of their corresponding variant '
+              'lookup table.'))
     parser.add_argument(
         '--output_avro_path',
         default='',
@@ -236,6 +240,10 @@ def validate(self, parsed_args, client=None):
         parsed_args.sharding_config_path, parsed_args.append)
 
     if parsed_args.sample_lookup_optimized_output_table:
+      if (parsed_args.output_table ==
+          parsed_args.sample_lookup_optimized_output_table):
+        raise ValueError('sample_lookup_optimized_output_table cannot be the '
+                         'same as output_table.')
       self._validate_output_tables(
           client, parsed_args.sample_lookup_optimized_output_table,
           parsed_args.sharding_config_path, parsed_args.append)
@@ -245,7 +253,7 @@ def _validate_output_tables(self, client,
                               sharding_config_path, append):
     if (output_table_base_name !=
         bigquery_util.get_table_base_name(output_table_base_name)):
-      raise ValueError(('Output table cannot contain "{}" we reserve this  '
+      raise ValueError(('Output table cannot contain "{}". we reserve this '
                         'string to mark sharded output tables.').format(
                             bigquery_util.TABLE_SUFFIX_SEPARATOR))
 
diff --git a/gcp_variant_transforms/vcf_to_bq.py b/gcp_variant_transforms/vcf_to_bq.py
index 7662534b1..ad4409b5c 100644
--- a/gcp_variant_transforms/vcf_to_bq.py
+++ b/gcp_variant_transforms/vcf_to_bq.py
@@ -563,7 +563,7 @@ def run(argv=None):
         known_args.output_table, suffixes)
     try:
       flatten_schema_file = tempfile.mkstemp(suffix=_BQ_SCHEMA_FILE_SUFFIX)[1]
-      if flatten_call_column.get_flatten_table_schema(flatten_schema_file) != 0:
+      if not flatten_call_column.get_flatten_table_schema(flatten_schema_file):
         raise ValueError('Failed to extract schema of flatten table')
       # Create output flatten tables if needed
       if not known_args.append: