def diffexp_topN(self, obsFilterA, obsFilterB, top_n=None):
"""
Computes the top N differentially expressed variables between two observation sets. If mode
is "TOP_N", then stats for the top N
dataframes
contain a subset of variables, then statistics for all variables will be returned, otherwise
only the top N vars will be returned.
:param obsFilterA: filter: dictionary with filter params for first set of observations
:param obsFilterB: filter: dictionary with filter params for second set of observations
:param top_n: Limit results to top N (Top var mode only)
:return: top N genes and corresponding stats
"""
if Axis.VAR in obsFilterA or Axis.VAR in obsFilterB:
raise FilterError("Observation filters may not contain variable conditions")
try:
shape = self.get_shape()
obs_mask_A = self._axis_filter_to_mask(Axis.OBS, obsFilterA["obs"], shape[0])
obs_mask_B = self._axis_filter_to_mask(Axis.OBS, obsFilterB["obs"], shape[0])
except (KeyError, IndexError):
raise FilterError("Error parsing filter")
if top_n is None:
top_n = self.dataset_config.diffexp__top_n
if self.server_config.exceeds_limit(
"diffexp_cellcount_max", np.count_nonzero(obs_mask_A) + np.count_nonzero(obs_mask_B)
):
raise ExceedsLimitError("Diffexp request exceeds max cell count limit")
result = self.compute_diffexp_ttest(obs_mask_A, obs_mask_B, top_n, self.dataset_config.diffexp__lfc_cutoff)
try:
return jsonify_numpy(result)
except ValueError:
raise JSONEncodingValueError("Error encoding differential expression to JSON")
def data_frame_to_fbs_matrix(self, filter, axis):
"""
Retrieves data 'X' and returns in a flatbuffer Matrix.
:param filter: filter: dictionary with filter params
:param axis: string obs or var
:return: flatbuffer Matrix
Caveats:
* currently only supports access on VAR axis
* currently only supports filtering on VAR axis
"""
if axis != Axis.VAR:
raise ValueError("Only VAR dimension access is supported")
try:
obs_selector, var_selector = self._filter_to_mask(filter)
except (KeyError, IndexError, TypeError, AttributeError):
raise FilterError("Error parsing filter")
if obs_selector is not None:
raise FilterError("filtering on obs unsupported")
num_columns = self.get_shape()[1] if var_selector is None else np.count_nonzero(var_selector)
if self.server_config.exceeds_limit("column_request_max", num_columns):
raise ExceedsLimitError("Requested dataframe columns exceed column request limit")
X = self.get_X_array(obs_selector, var_selector)
col_idx = np.nonzero([] if var_selector is None else var_selector)[0]
return encode_matrix_fbs(X, col_idx=col_idx, row_idx=None)