I am comparing regions in the DNA on structural breaks in cancer patients and healthy people. I am trying to run a Kruskal-Wallis test (SciPy Stats) on the number of breaks for each region, to see if there is a difference between the two distributions. I am not sure if the input for the Kruskal - Wallis should be arrays (documentation), or a list of arrays (elsewhere on the internet).
First, I tried an array for sample+control like this:
controls = ['1', '2', '3', '4', '5']
samples = ['10', '20', '30', '40', '50']
n=0
for item in controls:
array_item = np.array([item, samples[n]])
kw_test = stats.mstats.kruskalwallis(array_item)
print(kw_test)
n+=1
That gave me the following output for all items:
(0.0, nan)
I also tried converting the individual datapoints in arrays, and then run the KW-test.
controls = ['1', '2', '3', '4', '5']
samples = ['10', '20', '30', '40', '50']
n=0
kw_results = []
for item in controls:
array_controls = np.array([item])
array_samples = np.array([samples[n]])
kw_test = stats.mstats.kruskalwallis(array_samples, array_controls)
kw_results.append(kw_test)
n+=1
print(kw_results)
That gave (1.0, 0.31731050786291404)
for all comparisons, even when I changed one of the lists drastically.
Digging deeper, I read that the input should be a list of arrays, so I thought that giving only two datapoints (one sample, one control) might have caused the '(0.0, nan)', so I tried that as well.
controls = ['1', '2', '3', '4', '5']
samples = ['10', '20', '30', '40', '50']
list_ = []
n=0
for item in controls:
array_item = np.array([item, samples[n]])
list_.append(array_item)
n+=1
kw_test = stats.mstats.kruskalwallis(list_)
print(kw_test)
That gave me this error:
TypeError: Not implemented for this type
Now I am not sure what format/type to use, hopefully anyone can help me out!
The scipy.stats.mstats.kruskalwallis module uses arrays. These can be arrays with an uneven number of observations.
If you have your data within a CSV file in separate columns, something like this should work:
import pandas
from scipy.stats import mstats
Data = pandas.read_csv("CSVfile.csv")
Col_1 = Data['Colname1']
Col_2 = Data['Colname2']
Col_3 = Data['Colname3']
Col_4 = Data['Colname4']
print("Kruskal Wallis H-test test:")
H, pval = mstats.kruskalwallis(Col_1, Col_2, Col_3, Col_4)
print("H-statistic:", H)
print("P-Value:", pval)
if pval < 0.05:
print("Reject NULL hypothesis - Significant differences exist between groups.")
if pval > 0.05:
print("Accept NULL hypothesis - No significant difference between groups.")