Compute TPA and protein concentration #10
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bin/compute_tpa.py
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| import click | ||
| import pandas as pd | ||
| from pandas import DataFrame, Series |
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| bin/compute_tpa.py | 6 |
| bin/compute_tpa.py | 9 |
| bin/compute_tpa.py | 12 |
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| import click | ||
| import pandas as pd | ||
| from pandas import DataFrame, Series | ||
| from pyopenms import * |
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| from pyopenms import * | ||
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| from bin.compute_ibaq import print_help_msg, parse_uniprot_name | ||
| from ibaq.ibaqpy_commons import PROTEIN_NAME, NORM_INTENSITY, SAMPLE_ID, CONDITION |
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| bin/compute_tpa.py | 17 |
| bin/compute_tpa.py | 18 |
| bin/compute_tpa.py | 20 |
| bin/compute_tpa.py | 21 |
| bin/compute_tpa.py | 22 |
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| bin/compute_tpa.py | 41 |
| bin/compute_tpa.py | 61 |
| bin/compute_tpa.py | 75 |
| bin/compute_tpa.py | 83 |
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| import numpy as np | ||
| import os | ||
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| @click.command() |
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bin/compute_tpa.py
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| :return: | ||
| """ | ||
| if peptides is None or fasta is None: | ||
| print_help_msg(ibaq_compute) |
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F405: 'ibaq_compute' may be undefined, or defined from star imports: pyopenms
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| File Path | Line Number |
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| bin/compute_tpa.py | 49 |
| bin/compute_tpa.py | 53 |
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bin/compute_tpa.py
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| if name in proteins: | ||
| mw = AASequence().fromString(entry.sequence).getMonoWeight() | ||
| mw_dict[name] = mw | ||
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bin/compute_tpa.py
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| target_histones = histone_df[histone_df["name"] == organism.lower()] | ||
| genome_size = target_histones["genome_size"].values[0] | ||
| histones_list = target_histones["histone_entries"].values[0] | ||
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bin/compute_tpa.py
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| res["TPA"] = res["NormIntensity"] / res["MolecularWeight"] | ||
| plot_distributions(res, "TPA", SAMPLE_ID, log2=True) | ||
| plot_box_plot(res, "TPA", SAMPLE_ID, log2=True, | ||
| title="TPA Distribution", violin=False) |
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bin/compute_tpa.py
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| plot_distributions(res, "Concentration[nM]", SAMPLE_ID, log2=True) | ||
| plot_box_plot(res, "Concentration[nM]", SAMPLE_ID, log2=True, | ||
| title="Concentration[nM] Distribution", violin=False) |
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bin/compute_tpa.py
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| # calculate protein weight(ng) and concentration(nM) | ||
| if ruler: | ||
| avogadro = 6.02214129e23 | ||
| average_base_pair_mass = 617.96 # 615.8771 |
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| File Path | Line Number |
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| bin/compute_tpa.py | 85 |
| bin/compute_tpa.py | 86 |
| bin/compute_tpa.py | 93 |
| bin/compute_tpa.py | 94 |
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| res["MolecularWeight"] = res["MolecularWeight"].replace(0, 1) | ||
| res["TPA"] = res["NormIntensity"] / res["MolecularWeight"] | ||
| plot_distributions(res, "TPA", SAMPLE_ID, log2=True) | ||
| plot_box_plot(res, "TPA", SAMPLE_ID, log2=True, title="TPA Distribution", violin=False) |
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| res = res.groupby(["Condition"]).apply(proteomicRuler) | ||
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| plot_distributions(res, "Concentration[nM]", SAMPLE_ID, log2=True) | ||
| plot_box_plot(res, "Concentration[nM]", SAMPLE_ID, log2=True, title="Concentration[nM] Distribution", violin=False) |
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| histone_df = pd.read_json(open(os.path.split(__file__)[0] + os.sep + "histones.json", "rb")).T | ||
| target_histones = histone_df[histone_df["name"] == organism.lower()] | ||
| genome_size = target_histones["genome_size"].values[0] | ||
| histones_list = target_histones["histone_entries"].values[0] |
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