Reply to yang et al.: GCTA produces unreliable heritability estimates

Proceedings of the National Academy of Sciences of the United States of America

Volumn 113, Issue 32, 2016, Pages E4581-

  Kumar, Siddharth Krishna ^a   Feldman, Marcus W ^a   Rehkop, David H ^b   Tuljapurkar, Shripad ^a  

^a STANFORD UNIVERSITY   (United States)

^b STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GENOME WIDE COMPLEX TRAIT ANALYSIS; GENOME-WIDE ASSOCIATION STUDY; LETTER; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; MOLECULAR PHYLOGENY; PHENOTYPE; PRIORITY JOURNAL; SINGLE NUCLEOTIDE POLYMORPHISM;

GENOME-WIDE ASSOCIATION STUDY; POLYMORPHISM, SINGLE NUCLEOTIDE;

EID: 84982893680     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1608425113     Document Type: Letter

References (4)

1. Krishna Kumar S, Feldman MW, Rehkopf DH, Tuljapurkar S (2016) Limitations of GCTA as a solution to the missing heritability problem. Proc Natl Acad Sci USA 113(1):E61-E70.
2. Kumar SK, Feldman MW, Rehkopf DH, Tuljapurkar S (2016) Response to commentary on "Limitations of GCTA as a solution to the missing heritability problem." bioRxiv, 10.1101/039594.
3. Yang J, et al. (2010) Common SNPs explain a large proportion of the heritability for human height. Nat Genet 42(7):565-569.
4. Yang J, Lee SH, Wray NR, Goddard ME, Visscher PM (2016) GCTA-GREML accounts for linkage disequilibrium when estimating genetic variance from genome-wide SNPs. Proc Natl Acad Sci USA 113:E4579-E4580.