class Attribute(TwoCells):
def __init__(self, parent, text, value, callback=None, **kwargs):
super().__init__(parent, **kwargs)
self.callback = callback
self.label_text = StringVar()
self.label_text.set(text)
self.label = Label(self.frame, textvariable=self.label_text)
self.label.grid(column=0, row=0, padx=5, pady=5, sticky=W)
self.current_value = StringVar(self.frame)
self.current_value.set(value)
self.value = Entry(self.frame,
textvariable=self.current_value,
validate="key",
validatecommand=self.validate_command)
self.value.grid(column=1, row=0, padx=5, pady=5, sticky=E)
if self.callback:
self.value.bind("<KeyRelease>", self._on_entry_changed)
def _on_entry_changed(self, event):
self.callback()
def hide(self):
self.label.grid_remove()
self.value.grid_remove()
return self
def show(self, text):
self.label_text.set(text)
self.label.grid()
self.value.grid()
return self
def disable(self):
self.value.configure(state=DISABLED)
return self
def enable(self):
self.value.configure(state=NORMAL)
return self
def set(self, value):
self.current_value.set(value)
if str(value) == "":
self.disable()
else:
self.enable()
def get(self):
value = self.current_value.get()
if self.validation_type in [
TwoCells.INTEGERS, TwoCells.NON_NEGATIVE_INTEGERS
]:
return int(value) if value not in ["", "-"] else 0
else:
return value
class Dialogue(Frame):
def __init__(self):
super().__init__()
self.initUI()
def initUI(self):
self.style = Style()
self.style.theme_use("default")
self.master.title("LineChart")
self.pack(fill=BOTH, expand=True)
self.SSU = BooleanVar()
self.SSU.set(1)
self.COX1 = BooleanVar()
self.COX1.set(1)
self.EF1A = BooleanVar()
self.EF1A.set(1)
self.EF1A_variants = BooleanVar()
self.EF1A_variants.set(1)
self.filelabel = StringVar(self, "File not chosen")
self.filename = ""
self.var = IntVar()
self.var.set(1)
self.clades = IntVar()
self.clades.set(0)
# self.columnconfigure(2, weight=1)
# self.rowconfigure(2, weight=1)
cbSSU = Checkbutton(self,
text="SSU",
variable=self.SSU,
state=DISABLED,
onvalue=1,
offvalue=0)
cbSSU.select()
cbSSU.grid(sticky=W, padx=5, pady=5)
cbCOX1 = Checkbutton(self,
text="COX1",
variable=self.COX1,
onvalue=1,
offvalue=0)
cbCOX1.select()
cbCOX1.grid(sticky=W, row=1, padx=5, pady=5)
cbEF1A = Checkbutton(self,
text="EF1A",
variable=self.EF1A,
onvalue=1,
offvalue=0)
cbEF1A.select()
cbEF1A.grid(sticky=W, row=2, padx=5, pady=5)
cbEcomb = Checkbutton(self,
text="EF1A combinations",
variable=self.EF1A_variants,
onvalue=1,
offvalue=0)
cbEcomb.select()
cbEcomb.grid(sticky=W, row=3, padx=5, pady=5)
openButton = Button(self, text="Choose file", command=self.onOpen)
openButton.grid(sticky=W, row=0, column=1, padx=5, pady=5)
labFile = Label(self, textvariable=self.filelabel)
labFile.grid(sticky=W, row=0, column=2, columnspan=2, padx=5, pady=5)
closeButton = Button(self, text="Exit", command=self.quit)
closeButton.grid(sticky=E, row=4, column=3, padx=5, pady=5)
okButton = Button(self, text="OK", command=self.onOK)
okButton.grid(sticky=W, row=4, column=0, padx=5, pady=5)
def onOpen(self):
ftypes = [('Excel files', '*.xls, *.xlsx'), ('All files', '*')]
dlg = filedialog.Open(self, filetypes=ftypes)
file = dlg.show()
if file != '':
self.filelabel.set("Current file: " + file)
self.filename = file
self.readExcel(self.filename)
self.columns = BooleanVar()
self.columns.set(1)
if self.filelabel.get() != "File not chosen":
rboneColumn = Radiobutton(self,
text="Arrange in 1 column",
variable=self.columns,
value=1,
command=self.onClick)
rboneColumn.grid(sticky=W, row=2, column=1, padx=5, pady=5)
rb2Columns = Radiobutton(self,
text="Arrange in 2 columns",
variable=self.columns,
value=0,
command=self.onClick)
rb2Columns.grid(sticky=W, row=3, column=1, padx=5, pady=5)
def readExcel(self, filename):
self.dataframe = read_excel(filename, index_col="Specimen")
if self.clades.get() != 0:
self.labClades.grid_remove()
self.clades.set(len(set(self.dataframe.loc[:, "Clade"])))
self.labClades = Label(self,
text="Number of clades: " +
str(self.clades.get()))
self.labClades.grid(sticky=W, row=1, column=1, padx=5, pady=5)
def onClick(self):
if self.columns.get() == 0:
self.scale = Scale(self,
from_=1,
to=self.clades.get() - 1,
command=self.onScale,
orient=HORIZONTAL)
self.scale.grid(sticky=W, row=3, column=2)
self.labScale = Label(
self, text="Number of clades in the first column: ")
self.labScale.grid(sticky=W, row=2, column=2)
self.ScaleVal = Label(self, textvariable=self.var)
self.ScaleVal.grid(sticky=E, row=2, column=2)
else:
self.scale.grid_remove()
self.labScale.grid_remove()
self.ScaleVal.grid_remove()
def onScale(self, val):
v = int(float(val))
self.var.set(v)
# print(self.var.get())
def onOK(self):
dataframe = self.dataframe
SSU = self.SSU.get()
COX1 = self.COX1.get()
EF1A = self.EF1A.get()
EF1A_combinations = self.EF1A_variants.get()
change = self.var.get()
onecolumn = self.columns.get()
# graphical parameters: distance between columns and lines of variants, total height etc.
top = 200 # uppermost position
xS = 1 # X position of SSU column on the graph
xE = 2 # X position of EF1A column on the graph
xC = 0 # X position of COX1 column on the graph
cladeX = 3.3 # X position of clade names on the graph
distance = 5 # distance between lines
shift = 5 # distance between two columns
vardict = {}
ssu_set = set()
ef1a_set = set()
cox1_set = set()
# Count the number of specimens for each clade that have a valid SSU and at least one other valid gene variant
countdict = {}
for specimen in dataframe.index.values:
valid = 0
if findall("[A-Za-z]", str(dataframe.loc[specimen, "SSU"])) == []:
if EF1A and COX1:
if findall("[A-Za-z]", str(
dataframe.loc[specimen, "EF1A"])) == [] or findall(
"[A-Za-z]", str(dataframe.loc[specimen,
"COX1"])) == []:
valid = 1
elif EF1A:
if findall("[A-Za-z]", str(dataframe.loc[specimen,
"EF1A"])) == []:
valid = 1
elif COX1:
if findall("[A-Za-z]", str(dataframe.loc[specimen,
"COX1"])) == []:
valid = 1
if dataframe.loc[specimen, "Clade"] not in countdict:
countdict[dataframe.loc[specimen, "Clade"]] = valid
else:
countdict[dataframe.loc[specimen, "Clade"]] += valid
# build a dict of connections for every SSU variant, regardless of clades
for i in dataframe.index.values:
if findall("[A-Za-z]", str(dataframe.loc[
i, "SSU"])) == []: # choosing ony valid SSU variants
if dataframe.loc[i, "SSU"] not in vardict:
vardict[dataframe.loc[i, "SSU"]] = {
"SSU_count": 1,
"EF1A": {},
"COX1": {}
} # adding new SSU variant into dictionary
ssu_set.add(dataframe.loc[i, "SSU"])
else:
vardict[dataframe.loc[i, "SSU"]][
"SSU_count"] += 1 # increasing SSU variant count
if COX1:
if findall("[A-Za-z]", str(dataframe.loc[i, "COX1"])
) == []: # choosing ony valid COX1 variants
if dataframe.loc[i, "COX1"] not in vardict[
dataframe.loc[i, "SSU"]]["COX1"]:
vardict[dataframe.loc[i, "SSU"]]["COX1"][
dataframe.loc[
i, "COX1"]] = 1 # adding new COX1 variant
cox1_set.add(dataframe.loc[i, "COX1"])
else:
vardict[dataframe.loc[i, "SSU"]]["COX1"][
dataframe.loc[
i,
"COX1"]] += 1 # increasing COX1 variant count
if EF1A and EF1A_combinations:
if "homozygous" in str(dataframe.loc[i, "EF1A_combinations"]) \
or "both" in str(dataframe.loc[i, "EF1A_combinations"]) \
and findall("[A-Za-z]", str(dataframe.loc[
i, "EF1A"])) == []: # choosing ony homozygous EF1A variants or unique unknown heterozygous
if dataframe.loc[i, "EF1A"] not in vardict[
dataframe.loc[i, "SSU"]]["EF1A"]:
vardict[dataframe.loc[i, "SSU"]]["EF1A"][
dataframe.loc[
i, "EF1A"]] = 1 # adding new EF1A variant
ef1a_set.add(dataframe.loc[i, "EF1A"])
else:
vardict[dataframe.loc[i, "SSU"]]["EF1A"][
dataframe.loc[
i,
"EF1A"]] += 1 # increasing EF1A variant count
elif "+" in str(dataframe.loc[i, "EF1A_combinations"]
): # choosing known heterozygous variants
for var in findall(
"[0-9]+",
str(dataframe.loc[i, "EF1A_combinations"])):
if var not in vardict[dataframe.loc[
i, "SSU"]]["EF1A"]:
vardict[dataframe.loc[i, "SSU"]]["EF1A"][
var] = 1 # adding new EF1A variant
ef1a_set.add(int(var))
else:
vardict[dataframe.loc[i, "SSU"]]["EF1A"][
var] += 1 # increasing EF1A variant count
elif EF1A and findall("[A-Za-z]", str(
dataframe.loc[i, "EF1A"])) == []:
if dataframe.loc[i, "EF1A"] not in vardict[dataframe.loc[
i, "SSU"]]["EF1A"]:
vardict[dataframe.loc[i, "SSU"]]["EF1A"][dataframe.loc[
i, "EF1A"]] = 1 # adding new EF1A variant
ef1a_set.add(dataframe.loc[i, "EF1A"])
else:
vardict[dataframe.loc[i, "SSU"]]["EF1A"][dataframe.loc[
i, "EF1A"]] += 1 # increasing EF1A variant count
# print(vardict)
# # modify dataframe by adding known heterozygous variants into EF1A column.
new_dataframe = dataframe
if EF1A_combinations:
for i in range(len(new_dataframe["EF1A_combinations"])):
if "+" in str(new_dataframe["EF1A_combinations"][i]):
if len(
findall("[0-9]+",
str(new_dataframe["EF1A_combinations"]
[i]))) == 1:
new_dataframe.loc[
new_dataframe.index.values[i], "EF1A"] = int(
findall(
"[0-9]+",
str(new_dataframe["EF1A_combinations"][i]))
[0])
elif len(
findall("[0-9]+",
str(new_dataframe["EF1A_combinations"]
[i]))) == 2:
new_dataframe.loc[
new_dataframe.index.values[i], "EF1A"] = int(
findall(
"[0-9]+",
str(new_dataframe["EF1A_combinations"][i]))
[0])
new_dataframe = new_dataframe.append(
new_dataframe.iloc[i], ignore_index=True)
new_dataframe.loc[
new_dataframe.index.values[-1], "EF1A"] = int(
findall(
"[0-9]+",
str(new_dataframe["EF1A_combinations"][i]))
[1])
new_dataframe.loc[new_dataframe.index.values[-1],
"COX1"] = ""
grouping_columns = ["Clade", "SSU"]
if COX1:
grouping_columns.append("COX1")
if EF1A:
grouping_columns.append("EF1A")
grouped = new_dataframe.groupby(grouping_columns).aggregate(
{"SSU": "count"})
# print(grouped)
# starting Y coordinates
yS = top
yE = top
yC = top
# dictionaries with pairs of coordinates for every variant of every gene
ssu_coo = {}
cox1_coo = {}
ef1a_coo = {}
clade_coo = {}
# sets of clades and variants that were catalogued already to avoid duplicates
clade_done = set()
ssu_done = set()
cox1_done = set()
ef1a_done = set()
# Gives XY coordinates to every genetic variant iterating through clades.
# Variants are sorted acending; clades are sorted alphabetically
counter = 0
# adjusting distance between columns by adding the size of the longest clade name length
shift_adj = 0.1 * max(
[len(i) for i in grouped.index.get_level_values("Clade")]) + 0.3
shift += shift_adj
for clade in grouped.index.get_level_values("Clade"):
if clade not in clade_done:
if not onecolumn and counter == change: # if a specified change value is reached, starts the second column with a specified shift
xS += shift
yS = top
if COX1:
xC += shift
yC = top
if EF1A:
xE += shift
yE = top
cladeX += shift
counter += 1
yS -= distance
if COX1:
yC -= distance
if EF1A:
yE -= distance
# add coordinates of the clade name and vertical line at the side
ssuvalid = set([
i
for i in grouped.loc[(clade)].index.get_level_values("SSU")
if findall("[A-Za-z]", str(i)) == [] and str(i) != ""
])
if COX1:
cox1valid = set([
i for i in grouped.loc[(
clade)].index.get_level_values("COX1")
if findall("[A-Za-z]", str(i)) == [] and str(i) != ""
])
if EF1A:
ef1avalid = set([
i for i in grouped.loc[(
clade)].index.get_level_values("EF1A")
if findall("[A-Za-z]", str(i)) == [] and str(i) != ""
])
genelenlist = [len(ssuvalid)]
if COX1:
genelenlist.append(len(cox1valid))
if EF1A:
genelenlist.append(len(ef1avalid))
cladeY = yS - (max(genelenlist) - 1) * distance * 0.5
linestart = yS + 0.5 * distance
lineend = yS - (max(genelenlist) -
1) * distance - 0.5 * distance
clade_coo[clade] = [
cladeX, cladeY, cladeX - 0.2, linestart, lineend,
countdict[clade]
]
# within-clade vertical position adjustments
if COX1 and not EF1A:
if len(ssuvalid) - len(cox1valid) >= 2:
yC -= distance * (len(ssuvalid) - len(cox1valid)) // 2
elif len(cox1valid) - len(ssuvalid) >= 2:
yS -= distance * (len(cox1valid) - len(ssuvalid)) // 2
elif EF1A and COX1:
if len(ssuvalid) - len(cox1valid) >= 2:
yC -= distance * (len(ssuvalid) - len(cox1valid)) // 2
if len(ssuvalid) - len(ef1avalid) >= 2:
yE -= distance * (len(ssuvalid) -
len(ef1avalid)) // 2
elif len(ef1avalid) - len(ssuvalid) >= 2:
yS -= distance * (len(ef1avalid) -
len(ssuvalid)) // 2
yC -= distance * (len(ef1avalid) -
len(ssuvalid)) // 2
elif len(cox1valid) - len(ssuvalid) >= 2:
yS -= distance * (len(cox1valid) - len(ssuvalid)) // 2
if len(cox1valid) - len(ef1avalid) >= 2:
yE -= distance * (len(cox1valid) -
len(ef1avalid)) // 2
elif len(ef1avalid) - len(cox1valid) >= 2:
yC -= distance * (len(ef1avalid) -
len(cox1valid)) // 2
yS -= distance * (len(ef1avalid) -
len(cox1valid)) // 2
elif len(ef1avalid) - len(ssuvalid) >= 2:
yS -= distance * (len(ef1avalid) - len(ssuvalid)) // 2
yC -= distance * (len(ef1avalid) - len(cox1valid)) // 2
elif len(ssuvalid) - len(ef1avalid) >= 2:
yE -= distance * (len(ssuvalid) - len(ef1avalid)) // 2
elif EF1A:
if len(ssuvalid) - len(ef1avalid) >= 2:
yE -= distance * (len(ssuvalid) - len(ef1avalid)) // 2
elif len(ef1avalid) - len(ssuvalid) >= 2:
yS -= distance * (len(ef1avalid) - len(ssuvalid)) // 2
# finally, assign coordinates
for ssu in grouped.loc[(clade)].index.get_level_values("SSU"):
if findall("[A-Za-z]", str(ssu)) == [] and str(
ssu
) != "": # choose only valid genetic variants (no text, only numbers)
if ssu not in ssu_done:
ssu_coo[ssu] = [xS, yS]
yS -= distance
ssu_done.add(ssu)
if COX1:
for cox1 in grouped.loc[(
clade)].index.get_level_values("COX1"):
if findall("[A-Za-z]", str(cox1)) == [] and str(
cox1
) != "": # choose only valid genetic variants (no text, only numbers)
if cox1 not in cox1_done:
cox1_coo[cox1] = [xC, yC]
yC -= distance
cox1_done.add(cox1)
if EF1A:
for ef1a in grouped.loc[(
clade)].index.get_level_values("EF1A"):
if findall("[A-Za-z]", str(ef1a)) == [] and str(
ef1a
) != "": # choose only valid genetic variants (no text, only numbers)
if ef1a not in ef1a_done:
ef1a_coo[ef1a] = [xE, yE]
yE -= distance
ef1a_done.add(ef1a)
clade_done.add(clade)
geneXlist = [xS]
geneYlist = [yS]
if COX1:
geneXlist.append(xC)
geneYlist.append(yC)
if EF1A:
geneXlist.append(xE)
geneYlist.append(yE)
lowest = min(geneYlist)
yS = lowest
yC = lowest
yE = lowest
# print(grouped)
# Building a plot
def choose_line(size): # a rule for choosing line width for the plot
size = int(size)
if size in (1, 2):
width = 1
elif size == 3:
width = 1.5
elif size < 6:
width = 2
elif size < 11:
width = 2.5
else:
width = 3
return width
# remove axes
ax1 = axes(frameon=False)
ax1.set_frame_on(False)
ax1.get_xaxis().set_visible(False)
ax1.get_yaxis().set_visible(False)
# build the lines between genetic variants
for ssu in vardict:
if EF1A:
for ef1a in vardict[ssu]["EF1A"]:
if findall("[A-Za-z]", str(ef1a)) == []:
size = vardict[ssu]["EF1A"][ef1a]
plot([
ef1a_coo[int(ef1a)][0] + 0.4, ssu_coo[ssu][0] + 0.5
], [ef1a_coo[int(ef1a)][1], ssu_coo[ssu][1]],
linestyle="dashed" if size == 1 else "solid",
linewidth=choose_line(size),
color="black")
text(ef1a_coo[int(ef1a)][0] + 0.7,
ef1a_coo[int(ef1a)][1],
ef1a,
ha="center",
va="center")
if COX1:
for cox1 in vardict[ssu]["COX1"]:
if findall("[A-Za-z]", str(cox1)) == []:
size = vardict[ssu]["COX1"][cox1]
plot([cox1_coo[cox1][0], ssu_coo[ssu][0]],
[cox1_coo[cox1][1], ssu_coo[ssu][1]],
linestyle="dashed" if size == 1 else "solid",
linewidth=choose_line(vardict[ssu]["COX1"][cox1]),
color="black")
text(cox1_coo[cox1][0] - 0.3,
cox1_coo[cox1][1],
cox1,
ha="center",
va="center")
text(ssu_coo[ssu][0] + 0.25,
ssu_coo[ssu][1],
ssu,
ha="center",
va="center")
# add gene names above the variants for the second column
if not onecolumn:
text(xS - shift + 0.25, top + distance + 0.2, "SSU", ha="center")
text(xS + 0.25, top + distance + 0.2, "SSU", ha="center")
if EF1A:
text(xE - shift + 0.7,
top + distance + 0.2,
"EF1A",
ha="center")
text(xE + 0.7, top + distance + 0.2, "EF1A", ha="center")
if COX1:
text(xC - shift - 0.3,
top + distance + 0.2,
"COI",
ha="center")
text(xC - 0.3, top + distance + 0.2, "COI", ha="center")
else:
text(xS + 0.25, top + distance + 0.2, "SSU", ha="center")
if EF1A:
text(xE + 0.7, top + distance + 0.2, "EF1A", ha="center")
if COX1:
text(xC - 0.3, top + distance + 0.2, "COI", ha="center")
# add clade names and vertical lines to the right of the column
for clade in clade_coo:
if EF1A:
text(clade_coo[clade][0],
clade_coo[clade][1],
"%s (%d)" % (clade, clade_coo[clade][5]),
ha="left",
va="center")
plot([clade_coo[clade][2], clade_coo[clade][2]],
[clade_coo[clade][3], clade_coo[clade][4]],
linewidth=2,
color="black")
else:
text(clade_coo[clade][0] - shift * 0.5 + shift_adj + 0.65,
clade_coo[clade][1],
"%s (%d)" % (clade, clade_coo[clade][5]),
ha="left",
va="center")
plot([
clade_coo[clade][2] - shift * 0.5 + shift_adj + 0.7,
clade_coo[clade][2] - shift * 0.5 + shift_adj + 0.7
], [clade_coo[clade][3], clade_coo[clade][4]],
linewidth=2,
color="black")
# set limits for X axis to avoid overlapping with legend
if not onecolumn and EF1A:
xlim(0, 14)
elif not onecolumn:
xlim(0, 12)
elif onecolumn and EF1A:
xlim(0, 7)
elif onecolumn:
xlim(0, 5)
# produce lines for a legend
leg_lines = [
Line2D([0], [0], color="black", linestyle="dashed", linewidth=1),
Line2D([0], [0], color="black", linewidth=1),
Line2D([0], [0], color="black", linewidth=1.5),
Line2D([0], [0], color="black", linewidth=2),
Line2D([0], [0], color="black", linewidth=2.5),
Line2D([0], [0], color="black", linewidth=3)
]
# plot legend
legend(leg_lines, ["1", "2", "3", "4-5", "6-10", "11-20"],
loc="upper right")
# show the plot
show()
def db_download():
file_url = 'http://gbic.webhosting.rug.nl/genbank_mf.tar.gz'
#file_url = 'https://downloads.sourceforge.net/project/multigeneblast/db/genbank_mf_test.rar?use_mirror=switch'
answer = askyesno(
'Confirmation',
'Database downloading will take a while, and the database will occuppy ~15 GB disk space.\n Are you sure?'
)
if not answer:
return
global APPDATA
currentdir = os.getcwd()
os.chdir(APPDATA)
#Check if database is not already present
if "genbank_mf.pal" in os.listdir("."):
answer = askyesno(
'File already present',
'Database appears to be present already. Overwrite?')
if not answer:
return
#Check if sufficient disk space is available
default_file_size = 357266739200
dbfilesize = int(get_remote_filesize(file_url))
if int(get_free_space(".")) < dbfilesize:
showerror('Error', 'Insufficient disk space available.\n15GB needed.')
return
#Open 'loading...' message
loading = Toplevel(frame, height=200, width=400)
loading.title("Download progress")
message = "Downloading: " + str(0) + "/ " + str(int(
dbfilesize / 1024)) + " kb\nPlease wait..."
a = Label(loading, text=message)
a.grid(row=1, column=1, padx=50, pady=50)
loading.bind("<Escape>", lambda e: "return")
frame.update()
#Download the MGB GenBank database
try:
req = urllib.request.urlopen(file_url)
except:
showerror(
'Error',
'File not found on server.\nPlease check your internet connection.'
)
return
loading.protocol('WM_DELETE_WINDOW', lambda: cancel_download(req, loading))
CHUNK = 128 * 1024
x = 0
with open("genbank_mf.tar.gz", 'wb') as fp:
while True:
message = "Downloading: " + str(x) + "/ " + str(
int(dbfilesize / 1024)) + " kb\nPlease wait..."
try:
a = Label(loading, text=message)
a.grid_remove()
frame.update()
a.grid(row=1, column=1, padx=20, pady=20)
frame.update()
chunk = req.read(CHUNK)
if not chunk:
break
fp.write(chunk)
x += 128
if x > int(dbfilesize / 1024):
x = int(dbfilesize / 1024)
except:
showerror('Error', 'Download interrupted.')
return
#Report download success
loading.destroy()
showinfo("Download finished", "Download completed successfully.")
#Extract the database TAR/GZ file
extracting = Toplevel(frame, height=200, width=400)
extracting.title("Database extraction")
message = "Extracting database.\nPlease wait..."
a = Label(extracting, text=message)
a.grid(row=1, column=1, padx=50, pady=50)
extracting.bind("<Escape>", lambda e: "return")
frame.update()
try:
tar = tarfile.open("genbank_mf.tar.gz")
extracting.protocol('WM_DELETE_WINDOW',
lambda: cancel_download(tar, extracting))
frame.update()
tar.extractall()
tar.close()
except:
showerror(
"Error",
"Error extracting database. Please try to extract it manually.")
extracting.destroy()
os.chdir(currentdir)
return
extracting.destroy()
os.chdir(currentdir)
showinfo(
"Extraction finished",
"Database extraction finished.\nYou can now use this database by selecting 'genbank_mf.pal' under 'Select database' in the 'File' menu."
)