{'fraction_non_alphanumeric': 0.026115342763873776, 'fraction_numerical': 0.001088139281828074, 'mean_word_length': 5.524822695035461, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Linkage analysis: principles and methods for the analysis of human quantitative traits.

Currently, mapping genes for complex human traits relies on two complementary approaches, linkage and association analyses. Both suffer from several methodological and theoretical limitations, which can considerably increase the type-1 error rate and reduce the power to map human quantitative trait loci (QTL). This review focuses on linkage methods for QTL mapping. It summarizes the most common linkage statistics used, namely Haseman-Elston-based methods, variance components, and statistics that condition on trait values. Methods developed more recently that accommodate the X-chromosome, parental imprinting and allelic association in linkage analysis are also summarized. The type-I error rate and power of these methods are discussed. Finally, rough guidelines are provided to help guide the choice of linkage statistics.