config.py

LABEL_TO_ALIAS = {
    0: "Nucleoplasm",
    1: "NuclearM",
    2: "Nucleoli",
    3: "NucleoliFC",
    4: "NuclearS",
    5: "NuclearB",
    6: "EndoplasmicR",
    7: "GolgiA",
    8: "IntermediateF",
    9: "ActinF",
    10: "Microtubules",
    11: "MitoticS",
    12: "Centrosome",
    13: "PlasmaM",
    14: "Mitochondria",
    15: "Aggresome",
    16: "Cytosol",
    17: "VesiclesPCP",
    19: "Negative",
    19: "Multi-Location",
}

COLORS = [
    "#f44336",
    "#e91e63",
    "#9c27b0",
    "#673ab7",
    "#3f51b5",
    "#2196f3",
    "#03a9f4",
    "#00bcd4",
    "#009688",
    "#4caf50",
    "#8bc34a",
    "#cddc39",
    "#ffeb3b",
    "#ffc107",
    "#ff9800",
    "#ff5722",
    "#795548",
    "#9e9e9e",
    "#607d8b",
    "#dddddd",
    "#212121",
    "#ff9e80",
    "#ff6d00",
    "#ffff00",
    "#76ff03",
    "#00e676",
    "#64ffda",
    "#18ffff",
]

MAPPED_COLORS = {
    "PlasmaM": "#607d8b",
    "Cytosol": "#8D4399",
    "EndoplasmicR": "#2196f3", #03a9f4
    "Microtubules": "#E54B3B",
    "Vesicles": "#e91e63",
    "GolgiA": "#CED853",
    "IntermediateF": "#ff9800",
    "ActinF": "#03a9f4",
    "Endosomes": "#2196f3", #009688
    "Peroxisomes": "#00bcd4",
    "Mitochondria": "#9ed41b",
    "LipidDrop": "#ff9e80",
    "CytoBodies": "#8bc34a", #
    #"Peroxisomes": "#673ab7",
    #"Endosomes": "#f44336",
    "Aggresome": "#F71919",
    "NuclearM": "#00e676",
    "Nucleoplasm": "#ffff00",
    "NuclearS": "#F5BF39", #
    "Nucleoli": "#EC742C",
    "NuclearB": "#856344",
    "NucleoliFC": "#dddddd",
}

ORGANELLES = ["Nucleoplasm","Nucleoli","NucleoliFC","NuclearS","NuclearB","NuclearM",
              "Centrosome", "Aggresome","GolgiA", "Vesicles","Peroxisomes","Endosomes","Mitochondria",
              "LipidDrop","CytoBodies",
              "IntermediateF","EndoplasmicR","ActinF",
              "Cytosol","Microtubules","PlasmaM"]

ORGANELLES_FULLNAME = ["Nucleoplasm","Nucleoli","Nucleoli fibrillar center","Nuclear speckles","Nuclear bodies","Nuclear membrane",
              "Centrosome","Aggresome","Golgi apparatus", "Vesicles","Peroxisomes","Endosomes","Mitochondria",
              "Lipid droplets","Cytoplasmic bodies",
              "Intermediate filaments","Endoplasmic reticulum","Actin filaments",
              "Cytosol","Microtubules","Plasma membrane"]

# >>>>>>>>>>>>>>>>>>>>> PARAM CONFIGS
CELL_LINE =  "K-562" #"B2AI", "S-BIAD34", "U2OS", "S-BIAD34", "Hep-G2", "Hep-G2", "A-431", "HEL", "MCF7", "U-251 MG", "A-431", "RT4"
N_COEFS = 128 # number of fft coefficients for nucleus and cell contours
N_SAMPLES = -1 # -1 for all cells, or specify a number like 10000
N_CV = 1
MODE = "cell_nuclei"  # ["nuclei", "cell_nuclei"]
ALIGNMENT = "fft_cell_major_axis_polarized" # ["fft_nuclei_major_axis","fft_nuclei_major_axis","fft_cell_nuclei_centroid"]
COEF_FUNC = "fft" # ["efd", "wavelet"]
N_ISOS = [10,20] # number of concentric rings for nucleus and cytosolic regions
N_LANDMARKS = 32 # number of landmarks for each nucleus and cell contour

# >>>>>>>>>>>>>>>>>>>>> COMPUTE RESOURCE + PACKAGE
SERVER = "local"
if SERVER == "callisto":
    PROJECT_DIR = f"/data/2Dshapespace/{CELL_LINE.replace(' ','_')}"
    META_PATH = "/data/kaggle-dataset/publicHPA_umap/results/webapp/sl_pHPA_15_0.05_euclidean_100000_rmoutliers_ilsc_3d_bbox_rm_border.csv"
elif SERVER == "sherlock":
    PROJECT_DIR = f"/scratch/groups/emmalu/2Dshapespace/{CELL_LINE.replace(' ','_')}"
    META_PATH = "/scratch/groups/emmalu/sl_pHPA_15_0.05_euclidean_100000_rmoutliers_ilsc_3d_bbox_rm_border.csv"
else:
    PROJECT_DIR = f"./{CELL_LINE}"
    META_PATH = f"./{CELL_LINE}/meta_k562.csv" # your own metadata to perform downstream analysis