HESS¶

HESS (Heritability Estimation from Summary Statistics) is a software package for estimating and visualizing local SNP-heritability and genetic covariance (correlation) from GWAS summary association data. The latest version is version 0.5.3-beta. Reference panel can be downloaded here.

Software requirement¶

For running HESS¶

Python 2.7
NumPy 1.9+
Pandas 0.18+
PySnpTools 0.3+
SciPy 0.16+

For running analysis and visualization tools¶

Python 2.7
NumPy 1.9+
Pandas 0.18+
Matplotlib 1.4+
SciPy 0.16+

( Note: It is important to use the latest version of NumPy, which is more numerically stable when performing eigendecomposition of the LD matrix. Python 3.0+ may not work well ith HESS, which is written and tested in Python 2.7.3. )

References¶

Local SNP-heritability: Shi, Huwenbo, Gleb Kichaev, and Bogdan Pasaniuc. "Contrasting the genetic architecture of 30 complex traits from summary association data." The American Journal of Human Genetics 99, no. 1 (2016): 139-153.
Local genetic covariance (correlation): Shi, Huwenbo, Nicholas Mancuso, Sarah Spendlove, and Bogdan Pasaniuc. "Local genetic correlation gives insights into the shared genetic architecture of complex traits." The American Journal of Human Genetics 101, no. 5 (2017): 737-751.

Contact¶

Huwenbo Shi: shihuwenbo_AT_ucla.edu
Bogdan Pasaniuc: bpasaniuc_AT_mednet.ucla.edu