# ##### MAIN SETTINGS ########
# settings that affect data processing
selected_reader: mqreader # which file reader should be used
selected_normalizer: null # which normalizer should be used
has_techrep: false # does the file have technical replicates (can be "true" or "false")
use_protein_id: false # should the protein id be used (can be "true" or "false"), or TODO
equal_variance: false # should equal variance be assumed for the t-test? (can be "true" or "false")
pathways: [] # list of pathways which should be analyzed
go_terms: [] # list of go_terms which should be analyzed
mqreader:
index_col: "Gene name" # default and so far only option that works stably
duplicate_handling: "sum" # how should proteins with duplicate index_col be treated ? can be sum or drop
drop_columns: [] # string or list of samples that should be dropped
all_replicates: [] # list of all replicates
analysis_design: null # mapping of the analysis design organized ad tree structure
levels: null # int giving the number of levels
level_names: null # list of level names (e.g. 0, 1, 2, 3)
# ###### PLOT CREATION SETTINGS #######
# settings that determine which results will be created
# required arguments to create a plot are only the plot function "plot_...", create_plot, dfs_to_use, and levels.
plot_normalization_overview_all_normalizers_settings:
create_plot: false
dfs_to_use: []
levels: []
quantile_range: null # Optional[np.array] e.g.: np.arrange(0.05, 1, 0.05)
height: 15 # height if the figure
intensity_label: "Intensity" # name of the experiment
plot_heatmap_overview_all_normalizers_settings:
create_plot: false
dfs_to_use: []
levels: []
sort_index: false # should proteins be sorted alphanumerically
sort_index_by_missing: true # should proteins be sorted by missing values
sort_columns_by_missing: true # should samples be sorted by missing values
cmap: "autum_r" # color map to use for heatmap coloring
cmap_bad: "dimgray" # color for missing values
cax: null # plt.Axes, axis for the color bar
plot: null # Optional[Tuple[plt.Figure, plt.Axes]] --> figure to put plot
vmax: null # Optional[float]
vmin: null # Optional[float]
intensity_label: "Intensity" # name of the experiment
show_suptitle: true # should a figure title be shown
plot_detection_counts_settings:
create_plot: false
dfs_to_use: []
levels: []
intensity_label: "Intensity" # name of the experiment
show_suptitle: true # should a figure title be shown
plot_detected_proteins_per_replicate_settings:
create_plot: false
dfs_to_use: []
levels: []
intensity_label: "Intensity" # name of the experiment
show_suptitle: true # should a figure title be shown
plot_venn_results_settings:
create_plot: false
dfs_to_use: []
levels: []
show_suptitle: true # should a figure title be shown
title_font_size: 20 # font size of the figure title
set_label_font_size: 16 # font size of the text labels
subset_label_font_size: 14 # font size of the numbers
plot_venn_groups_settings:
create_plot: false
dfs_to_use: []
levels: []
show_suptitle: true # should a figure title be shown
title_font_size: 20 # font size of the figure title
set_label_font_size: 16 # font size of the text labels
subset_label_font_size: 14 # font size of the numbers
plot_pca_overview_settings:
create_plot: false
dfs_to_use: []
levels: []
no_missing_values: true # should missing values be neglected? (can be "true" or "false")
n_components: 2 # how many principal components should be calculated
fill_na_before_norm: false # if data should be interpolated, should this be done before normalisation
fill_value: 0 # if data should be interpolated, which fill value should be used
normalize: true # should transformed data be normalized with the singular values before plotting
intensity_label: "Intensity" # name of the experiment
color_map: null # Optional[dict]: a mapping from the column names to a color
show_suptitle: true # should a figure title be shown
marker_size: 150 # size of the points in the scatter plots
legend_marker_size: 12 # size of the legend marker
plot_intensity_histograms_settings:
create_plot: false
dfs_to_use: []
levels: []
intensity_label: "Intensity" # name of the experiment
show_suptitle: true # should a figure title be shown
compare_to_remaining: false # should the sample be compared to the overall samples
legend: false # should a legend for the samples be displayed
n_bins: 25 # how many bins should the histograms have
show_mean: true # should the mean intensity be indicated
histtype: "bar" # type of histogram: can be "bar", "barstacked" "step", "stepfilled"
color: null # string or list of any matplotlib supported color
plot: null # Optional[Tuple[plt.Figure, plt.Axes]] --> figure to put plot
plot_relative_std_settings:
create_plot: false
dfs_to_use: []
levels: []
experiment_name: "" # string: name of the overall experiment
intensity_label: "Intensity" # name of the intensities for the x label
show_suptitle: true # should a figure title be shown
bins: (10, 20, 30) # in which bins should the standard deviations be categorized
cmap: null # dict: mapping for the digitized labels to a color
# example: default_cm = {0: "navy", 1: "royalblue", 2: "skyblue", 3: "darkgray"}
plot_scatter_replicates_settings:
create_plot: false
dfs_to_use: []
levels: []
intensity_label: "Intensity" # name of the experiment
show_suptitle: false # should a figure title be shown
plot_experiment_comparison_settings:
create_plot: false
dfs_to_use: []
levels: []
intensity_label: "Intensity" # name of the experiment
show_suptitle: true # should a figure title be shown
plot: null # Optional[Tuple[plt.Figure, plt.Axes]] --> figure to put plot
plot_rank_settings:
create_plot: false
dfs_to_use: []
levels: []
intensity_label: "Intensity" # name of the experiment
full_name: "Experiment" # which data node/group of samples should be compared
show_suptitle: true # should a figure title be shown
plot_pathway_analysis_settings:
create_plot: false
dfs_to_use: []
levels: []
equal_var: true
show_suptitle: true # should a figure title be shown
threshold: 0.05 # maximum p value indicating significance
intensity_label: "Intensity" # name of the intensities for the x label
color_map: null # Optional[dict]: a mapping from the column names to a color
plot_go_analysis_settings:
create_plot: false
dfs_to_use: []
levels: []
show_suptitle: true # should a figure title be shown
intensity_label: "Intensity" # name of the experiment
plot_r_volcano_settings:
create_plot: false
dfs_to_use: []
levels: []
adj_pval: false # should the adjusted p-val be used? (can be "true" or "false")
sample1: null # string of the sample that should be analysed (left side/ down regulated)
sample2: null # string of the sample that should be analysed (right side/ up regulated)
intensity_label: "Intensity" # name of the experiment
show_suptitle: true # should a figure title be shown
pval_threshold: 0.05 # float: maximum p value indicating significance
fchange_threshold: 2 # float: min fold change threshold (before log2 transformation) to be labelled significant
scatter_size: 20 # float: size of the points in the scatter plots
n_labelled_proteins: 10 # int: number of points that will be marked in th plot