LD SCORE ESTIMATION
How can I estimate Ldscore for a particular population from 1000 genome with a minimal time. I tried computing with this code : python ~/ldsc/ldsc.py --bfile afr_phase3 --l2 --ld-wind-cm 1 --out Africa But it takes a lot of time and it is not actually showing if it is running or not. I need either a script or another suggestion.
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You might want to separate the bed files into chromosome before you run ldsc as that is the recommended way of doing it.
I separated my chromosomes into chunks and ran the analysis but it is still taking forever to finish so I also calculated PCs for my dataset and ran the analysis using a --cov flag: python ~/cov-ldsc/ldsc.py --bfile split22 --l2 --ld-wind-cm 20 --cov pca_results2.eigenvec --out covldscore_22 I got a dbug message:
T= T+np.dot(cov.iloc[:,i],Y[:,j])*cov.iloc[:,i] TypeError: can't multiply sequence by non-int of type 'float'
Please do I resolve this issue?
Never ran LDSC with a covariate before. Not sure what that'd achieve.
If you are using a 20CM window, LDSC will take forever to run. The recommended CM is 1~2. The higher the value, the longer it will take