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Using the human SNP p-values, VEGAS produced p-values for 17,787 human genes (the number of autosomal genes on the UCSC Genome Browser hg18 assembly).
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To infer reliable mutation patterns, we used the human genome and SNP data obtained from the HapMap database and dbSNP as well as the chimpanzee genome as outgroup (a reference).
First, MegaBLAST was used to map the human SNPs and their flanking sequences(100 bp on each side) to the four outgroup sequences (chimpanzee, gorilla, orangutan, gibbon)[ 28].
Using the SNPs of the human genome available in databases, we searched for SNPs within these genome-wide predicted EREs and explored their association with breast cancer.
The genetic variations in the coding regions are successfully evaluated in Tibetans and lowlanders by using human SNP arrays [ 3, 4] and human exon capture arrays [ 5].
To compare the pattern observed in the chimpanzee genome, we performed a similar analysis using the SNPs in the human genome.
To test this hypothesis, we used human SNP data to estimate the frequency of SNPs inside and outside the UCRs.
In this work, we attempt to address the question of whether HapMap SNPs are sufficient to capture most of the variation and untyped SNPs in the human genes by using the SNPs identified by National Institute of Environmental Health Sciences NIEHS SNPss)[ 24, 25].
This is similar to the number of CNVs per subject reported from most other studies that have used Affymetrix 6.0 Human SNP arrays [14].
SNP array analysis was performed using the Affymetrix Genome Wide Human SNP Array 6.0, which includes over 906 600 SNPs and more than 946 000 probes for the detection of CNVs.
SNP were genotyped using the Affymetrix genome-wide human SNP array 6.0.
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