remove other information.

ibaqpy/commands/compute_tpa.py

@@ -1,4 +1,3 @@
-
 import os
 import click
 import matplotlib.pyplot as plt
@@ -52,7 +51,7 @@ def handle_nonstandard_aa(aa_seq: str) -> (list, str):
 @click.option(
     "--verbose",
     help="Print addition information about the distributions of the intensities, number of peptides remove "
-    "after normalization, etc.",
+         "after normalization, etc.",
     is_flag=True,
 )
 @click.option(
@@ -61,15 +60,15 @@ def handle_nonstandard_aa(aa_seq: str) -> (list, str):
     default="TPA-QCprofile.pdf",
 )
 def tpa_compute(
-    fasta: str,
-    peptides: str,
-    ruler: bool,
-    organism: str,
-    ploidy: int,
-    cpc: float,
-    output: str,
-    verbose: bool,
-    qc_report: str,
+        fasta: str,
+        peptides: str,
+        ruler: bool,
+        organism: str,
+        ploidy: int,
+        cpc: float,
+        output: str,
+        verbose: bool,
+        qc_report: str,
 ) -> None:
     """
     This command computes the protein copies and concentrations according to a file output of peptides with the

ibaqpy/commands/datasets_merger.py

@@ -1,4 +1,3 @@
-
 import re
 
 import click
@@ -61,19 +60,19 @@
 )
 @click.pass_context
 def datasets_merge(
-    ctx,
-    data_folder: str,
-    output: str,
-    covariate: str,
-    organism: str,
-    covariate_to_keep: list,
-    non_missing_percent_to_keep: float,
-    skip_outliers_removal: bool,
-    n_components: int,
-    min_cluster: int,
-    min_sample_num: int,
-    n_iter: int,
-    verbose: bool,
+        ctx,
+        data_folder: str,
+        output: str,
+        covariate: str,
+        organism: str,
+        covariate_to_keep: list,
+        non_missing_percent_to_keep: float,
+        skip_outliers_removal: bool,
+        n_components: int,
+        min_cluster: int,
+        min_sample_num: int,
+        n_iter: int,
+        verbose: bool,
 ):
     if covariate_to_keep:
         covariate_to_keep = re.split(",\s*", covariate_to_keep)

ibaqpy/commands/tsne_visualization.py

@@ -131,7 +131,8 @@ def plot_tsne(df, x_col, y_col, hue_col, file_name):
 @click.option(
     "-o",
     "--pattern",
-    help="Protein file pattern",   #TODO: I think we should use instead of pattern the structure of quantms.io for absolute quantification
+    help="Protein file pattern",
+    # TODO: I think we should use instead of pattern the structure of quantms.io for absolute quantification
     required=False,
     default="proteins.tsv",
 )

ibaqpy/ibaqpyc.py

@@ -2,7 +2,6 @@
 
 from ibaqpy.commands.features2peptides import features2parquet
 from ibaqpy.commands.compute_tpa import tpa_compute
-from ibaqpy.commands.datasets_merger import datasets_merge
 from ibaqpy.commands.merge_condition_files import merge_condition_generation
 from ibaqpy.commands.peptides2proteins import peptides2proteins
 from ibaqpy.commands.tsne_visualization import tsne_visualization
@@ -24,7 +23,6 @@ def cli():
 
 
 cli.add_command(tpa_compute)
-# cli.add_command(datasets_merge)
 cli.add_command(features2parquet)
 cli.add_command(merge_condition_generation)
 cli.add_command(peptides2proteins)