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For example, recent progess using the HapMap resource has begun to illustrate the contribution of common genetic variants to natural variation in gene expression within and among major world populations.
The candidate gene approach, which requires a priori knowledge of certain biological processes or pathways, can be complemented by targeted deep resequencing to discover rarer variants, while the whole-genome approach using the HapMap resource can be used to identify new targets of interest in an unbiased way.
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The SNPs were selected to extract the most genetic information based on CHB haplotype data using the HAPMAP database (Hapmap Data Rel 27 Phase II+III, Feb09) [37].
We compared our Spanish frequencies to those of HapMap CEU subjects, using the HapMap minor allele as the reference (Figure 1).
LSBL in HapMap was calculated using the HapMap database that considers all African, European and Asian populations together.
We first compared the Daghestani and control populations with the HapMap samples (20 individuals each), performing a PCA using the HapMap SNPs from the neutral regions.
We restricted this evaluation to the two-step protocol using the HapMap phase II combined sample.
Using the HapMap-NIEHS overlapped SNPs; we indeed observe that the coverage is low in the NIEHS population as compared to the HapMap population.
Besides being used in traditional candidate gene approaches, the HapMap resource and technology for genome-wide analysis have enabled an unbiased approach to detect clinically important genetic factors that determine drug effectiveness and side effects between patients (Deloukas and Bentley, 2004; Andrawiss, 2005).
When the candidate gene is known, Jones et al. demonstrated that the HapMap resource is useful for pharmacogenetic discovery by using HapMap cell lines and HapMap SNPs to test whether a thiopurine methyltransferase (TPMT) polymorphism could be identified as predicting TPMT phenotype (Jones, Yang et al. 2007).
Utilizing the HapMap resource, these authors were able to use a genome-wide approach to evaluate associations between 1) genotype and drug response, 2) genotype and gene expression, and 3) gene expression and drug response.
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