def crossCompartmentCorr(dfA, dfB, method='pearson'):
"""Cytokine correlation for those that are common to both A and B"""
cyList = np.array([cy for cy in dfA.columns if cy in dfB.columns])
joinedDf = pd.merge(dfA[cyList], dfB[cyList], suffixes=('_A','_B'), left_index=True, right_index=True)
tmpCorr = np.zeros((len(cyList),3))
for i,cy in enumerate(cyList):
tmp = joinedDf[[cy + '_A',cy + '_B']].dropna()
tmpCorr[i,:2] = partialcorr(tmp[cy + '_A'], tmp[cy + '_B'], method=method)
sorti = np.argsort(tmpCorr[:,0])
tmpCorr = tmpCorr[sorti,:]
_, tmpCorr[:,2], _, _ = sm.stats.multipletests(tmpCorr[:,1], method='fdr_bh')
return pd.DataFrame(tmpCorr, index=cyList[sorti], columns=['rho','pvalue','qvalue'])
def meanCorr(cyDf, meanVar, cyList=None, method='pearson'):
"""Each cytokine's correlation with the mean."""
if cyList is None:
cyList = np.array([c for c in cyDf.columns if not c == meanVar])
cyList = np.asarray(cyList)
tmpCorr = np.zeros((len(cyList), 3))
for i, s in enumerate(cyList):
tmpCorr[i, :2] = partialcorr(cyDf[s], cyDf[meanVar], method=method)
sorti = np.argsort(tmpCorr[:, 0])
tmpCorr = tmpCorr[sorti,:]
_, tmpCorr[:, 2], _, _ = sm.stats.multipletests(tmpCorr[:, 1], alpha=0.2, method='fdr_bh')
return pd.DataFrame(tmpCorr, index=cyList[sorti], columns=['rho', 'pvalue', 'qvalue'])
def meanCorr(cyDf, meanVar, cyList=None, method='pearson'):
"""Each cytokine's correlation with the mean."""
if cyList is None:
cyList = np.array([c for c in cyDf.columns if not c == meanVar])
cyList = np.asarray(cyList)
tmpCorr = np.zeros((len(cyList),3))
for i,s in enumerate(cyList):
tmpCorr[i,:2] = partialcorr(cyDf[s], cyDf[meanVar], method=method)
sorti = np.argsort(tmpCorr[:,0])
tmpCorr = tmpCorr[sorti,:]
_, tmpCorr[:,2], _, _ = sm.stats.multipletests(tmpCorr[:,1], alpha=0.2, method='fdr_bh')
return pd.DataFrame(tmpCorr, index=cyList[sorti], columns=['rho','pvalue','qvalue'])
def crossCompartmentCorr(dfA, dfB, method='pearson'):
"""Cytokine correlation for those that are common to both A and B"""
cyList = np.array([cy for cy in dfA.columns if cy in dfB.columns])
joinedDf = pd.merge(dfA[cyList],
dfB[cyList],
suffixes=('_A', '_B'),
left_index=True,
right_index=True)
tmpCorr = np.zeros((len(cyList), 3))
for i, cy in enumerate(cyList):
tmp = joinedDf[[cy + '_A', cy + '_B']].dropna()
tmpCorr[i, :2] = partialcorr(tmp[cy + '_A'],
tmp[cy + '_B'],
method=method)
sorti = np.argsort(tmpCorr[:, 0])
tmpCorr = tmpCorr[sorti, :]
_, tmpCorr[:, 2], _, _ = sm.stats.multipletests(tmpCorr[:, 1],
method='fdr_bh')
return pd.DataFrame(tmpCorr,
index=cyList[sorti],
columns=['rho', 'pvalue', 'qvalue'])
