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Plotting in slingshot script is now disabled by default and can be en…
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…abled via a command line argument. Also fixes Murali-group#7
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@matthieubulte
matthieubulte committed Oct 9, 2019
1 parent c5ec584 commit 039e843
Showing 1 changed file with 86 additions and 83 deletions.
169 changes: 86 additions & 83 deletions scripts/runSlingshot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,9 +13,7 @@
from pathlib import Path
from sklearn.cluster import KMeans
from sklearn.manifold import TSNE
import matplotlib.pyplot as plt
from optparse import OptionParser
import seaborn as sns
from optparse import OptionParser

seed = 0
np.random.seed(seed)
Expand Down Expand Up @@ -46,19 +44,95 @@ def parseArgs(args):

parser.add_option('', '--noEnd', action='store_true',default= False,
help='Do not force SlingShot to have an end state.')



parser.add_option('-r', '--perplexity', type='int',default=500,
help='Perplexity for tSNE.')


parser.add_option('', '--enableDebugPlots', action='store_true', default=False,
help='Plot both the deterministic and slingshot pseudotime trajectories on top of '
'the original cell clustering.')

(opts, args) = parser.parse_args(args)

return opts, args



def computeSSPT(ExpDF, ptDF, nClust, outPaths, noEnd = False, perplexity = 500):
def plotResults(outPaths, tn, lneCnt, curveLst):
import matplotlib
matplotlib.use("TkAgg")

import matplotlib.pyplot as plt
import seaborn as sns

# Plot slingshot pseudotime
# and original clusters
f, axes = plt.subplots(2, 2, figsize=(7.5, 7.5))

detPT = pd.read_csv(outPaths + "/SlingshotPT.csv",
header=0, index_col=0)
print()
colNames = detPT.columns
for colName in colNames:
# Select cells belonging to each pseudotime trajectory
index = detPT[colName].index[detPT[colName].notnull()]
tn.loc[index, colName] = detPT.loc[index, colName]

sns.scatterplot(x='dim1', y='dim2',
data=tn.loc[index], hue=colName,
palette="viridis",
ax=axes[1][0])
plt.legend([])

for line in range(0, lneCnt, 2):
sns.lineplot(x=curveLst[line + 1], y=curveLst[line],
color="k", ax=axes[1][0])

sns.scatterplot(x='dim1', y='dim2',
data=tn, hue='kMeans',
palette="Set1",
ax=axes[1][1])

# Plot deterministic pseudotime
# and original clusters
detPT = pd.read_csv(outPaths + "/PseudoTime.csv",
header=0, index_col=0)
colNames = detPT.columns
for idx in range(len(colNames)):
# Select cells belonging to each pseudotime trajectory
colName = colNames[idx]
index = detPT[colName].index[detPT[colName].notnull()]
tn.loc[index, 'Original'] = int(idx)

tn['ExpTime'] = detPT.min(axis='columns')
tn.to_csv(outPaths + "/Updated_rd.tsv", sep='\t')

sns.scatterplot(x='dim1', y='dim2',
data=tn, hue='ExpTime',
palette="viridis",
ax=axes[0][0])

sns.scatterplot(x='dim1', y='dim2',
data=tn, hue='Original',
palette="Set1",
ax=axes[0][1])

axes[0][0].get_legend().remove()
axes[0][0].title.set_text('Experiment Time')
axes[0][1].get_legend().remove()
axes[0][1].title.set_text('Original Trajectories')

axes[1][0].get_legend().remove()
axes[1][0].title.set_text('Slingshot Pseudotime')

axes[1][1].get_legend().remove()
axes[1][1].title.set_text('kMeans Clustering')

f.tight_layout()

plt.savefig(outPaths + "/SlingshotOutput.png")


def computeSSPT(ExpDF, ptDF, nClust, outPaths, noEnd = False, perplexity = 500, plotting=False):
'''
Compute PseudoTime using 'slingshot'.
Needs the input GenexCells expression data frame.
Expand Down Expand Up @@ -120,11 +194,6 @@ def computeSSPT(ExpDF, ptDF, nClust, outPaths, noEnd = False, perplexity = 500):
print(cmdToRun)
os.system(cmdToRun)

# os.system("cp temp/PseudoTime.csv "+outPaths+"/SlingshotPT.csv")
# os.system("cp temp/curves.csv "+outPaths+"/curves.csv")
# os.system("cp temp/rd.tsv "+outPaths+"/rd.tsv")
# os.system("cp temp/cl.tsv "+outPaths+"/cl.tsv")

# Do this only for the first file
tn = pd.read_csv(outPaths+"/rd.tsv",
header = 0, index_col =None, sep='\t')
Expand All @@ -143,75 +212,9 @@ def computeSSPT(ExpDF, ptDF, nClust, outPaths, noEnd = False, perplexity = 500):
tn.columns = ['CellID','dim1','dim2','kMeans']
tn.index = tn.CellID

f, axes = plt.subplots(2, 2, figsize=(7.5, 7.5))

# Plot slingshot pseudotime
# and original clusters
detPT = pd.read_csv(outPaths+"/SlingshotPT.csv",
header = 0, index_col = 0)
print()
colNames = detPT.columns
for colName in colNames:
# Select cells belonging to each pseudotime trajectory
index = detPT[colName].index[detPT[colName].notnull()]
tn.loc[index,colName] = detPT.loc[index,colName]


sns.scatterplot(x='dim1',y='dim2',
data = tn.loc[index], hue = colName,
palette = "viridis",
ax = axes[1][0])
plt.legend([])

for line in range(0, lneCnt, 2):
sns.lineplot(x= curveLst[line+1],y=curveLst[line],
color = "k", ax = axes[1][0])

sns.scatterplot(x='dim1',y='dim2',
data = tn, hue = 'kMeans',
palette = "Set1",
ax = axes[1][1])

# Plot deterministic pseduotime
# and original clusters
detPT = pd.read_csv(outPaths+"/PseudoTime.csv",
header = 0, index_col = 0)
colNames = detPT.columns
for idx in range(len(colNames)):
# Select cells belonging to each pseudotime trajectory
colName = colNames[idx]
index = detPT[colName].index[detPT[colName].notnull()]
tn.loc[index,'Original'] = int(idx)

tn['ExpTime'] = detPT.min(axis='columns')

sns.scatterplot(x='dim1',y='dim2',
data = tn, hue = 'ExpTime',
palette = "viridis",
ax = axes[0][0])

#tn['Original'] = tn['Original'].astype('category')
sns.scatterplot(x='dim1',y='dim2',
data = tn, hue = 'Original',
palette = "Set1",
ax = axes[0][1])

axes[0][0].get_legend().remove()
axes[0][0].title.set_text('Experiment Time')
axes[0][1].get_legend().remove()
axes[0][1].title.set_text('Original Trajectories')

axes[1][0].get_legend().remove()
axes[1][0].title.set_text('Slingshot Pseudotime')

axes[1][1].get_legend().remove()
axes[1][1].title.set_text('kMeans Clustering')

f.tight_layout()

tn.to_csv(outPaths+"/Updated_rd.tsv",
sep='\t')
plt.savefig(outPaths+"/SlingshotOutput.png")
if plotting:
plotResults(outPaths, tn, lneCnt, curveLst)

os.system("rm -rf temp/")

def main(args):
Expand All @@ -222,7 +225,7 @@ def main(args):

# Compute PseudoTime using slingshot
# TODO: Add other methods
computeSSPT(ExprDF, ptDF, opts.nClusters, opts.outPrefix, opts.noEnd, opts.perplexity)
computeSSPT(ExprDF, ptDF, opts.nClusters, opts.outPrefix, opts.noEnd, opts.perplexity, opts.enableDebugPlots)

if __name__ == "__main__":
main(sys.argv)

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