The BOLT-LMM software package computes statistics for association between phenotype and genotypes using a linear mixed model (LMM) [1]. By default, BOLT-LMM assumes a Bayesian mixture-of-normals prior for the random effect attributed to SNPs other than the one being tested. This model generalizes the standard "infinitesimal" mixed model used by existing mixed model association methods (e.g., EMMAX [2], FaST-LMM [3-6], GEMMA [7], GRAMMAR-Gamma [8], GCTA-LOCO [9]), providing an opportunity for increased power to detect associations while controlling false positives. Additionally, BOLT-LMM applies algorithmic advances to compute association statistics much faster than existing methods, both when using the Bayesian mixture model and when specialized to standard mixed model association.

BOLT-LMM v1.0 User Manual12

BOLT-LMM v1.0 User Manual

Ingredients 600 millilitres warm water 2 tablespoons honey (can substitute with molasses) 800 grams plain flour, plus extra for dusting 200 grams whole-wheat flour 1 teaspoon salt 14 grams instant dry yeast Vegetable oil, for oiling the bowl Method Combine the water and honey in a small bowl, and stir to dissolve the honey.

Test publicatio n

We examine whether having previously been self-employed is a negative signal on the job market. In a UK field experiment where two applications of otherwise equally qualified individuals were sent out in response to the same vacancies in human resource management, we find that entrepreneurs systematically receive fewer responses than non-entrepreneurs. Empirical studies that treat market wages as the opportunity cost of remaining self-employed are therefore likely to overestimate alternative earnings to entrepreneurship.