Linkage disequilibrium — understanding the evolutionary past and mapping the medical future

By M. Slatkin. 2008

1,510 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology, Computational Biology & Bioinformatics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

1. Jose Padial
2. Tomaz Berisa
3. I. J. De la Riva
4. S. Cloutier
5. Braulio J. Soto-Cerda
6. M. Vences
7. Aurélien Miralles
8. Joseph K. Pickrell

In Molecular Biology

1. Sune Frankild
2. Janos X. Binder
3. Kalliopi Tsafou
4. I. J. De la Riva
5. Jose Padial
6. Albert Pallejà
7. Lars Juhl Jensen
8. M. Vences

In Computational Biology & Bioinformatics

1. Braulio J. Soto-Cerda
2. I. J. De la Riva
3. Eric J. Topol
4. Aurélien Miralles
5. S. Cloutier
6. Lars Juhl Jensen
7. Joseph K. Pickrell
8. Jose Padial

Citations in the corpus

• Association Mapping in Plant Genomes (2012, methodology): “Simply stated, if alleles at two loci are in LD and they both affect positively reproductive fitness, the response to selection at one locus might be accelerated by selection affecting the other (Slatkin, 2008).”
• LDlinkR: An R Package for Rapidly Calculating Linkage Disequilibrium Statistics in Diverse Populations (2020, background): “Population geneticists calculate LD to assess population structure and population history (Mueller, 2004) and LD analysis can be employed to detect natural selection and estimate allelic age (Slatkin, 2008).”
• Approximately independent linkage disequilibrium blocks in human populations (2015, background): “In reality, matrix P turns out to be sparse, approximately banded, and approximately block-diagonal, with sporadically overlapping blocks [Slatkin, 2008; Wen and Stephens, 2010].”
• DISEASES: Text mining and data integration of disease–gene associations (2014, background): “For this reason GWAS results must be analyzed in the context of linkage disequilibrium (LD), which is defined as the non-random association of variants at two or more loci [31,32].”
• Genome-wide association studies in diverse populations (2010, background): “It was hoped that each true disease SNP not genotyped in a study would be 'captured' through a minimal level of statistical association, or linkage disequilibrium (LD”
• Human genetic variation and its contribution to complex traits (2009, background): “This correlation structure, or linkage disequilibrium (LD”
• The integrative future of taxonomy (2010, methodology): “situation termed linkage disequilibrium [99]- and this method can be applied to”