scholarly journals Batch effects in the BRLMM genotype calling algorithm influence GWAS results for the Affymetrix 500K array

2010 ◽  
Vol 10 (4) ◽  
pp. 336-346 ◽  
Author(s):  
K Miclaus ◽  
R Wolfinger ◽  
S Vega ◽  
M Chierici ◽  
C Furlanello ◽  
...  
Keyword(s):  
Batch Effects ◽  
Genotype Calling ◽  
Calling Algorithm ◽  
500K Array

scholarly journals PanCGH: a genotype-calling algorithm for pangenome CGH data

2009 ◽  
Vol 25 (3) ◽  
pp. 309-314 ◽  
Author(s):  
Jumamurat R. Bayjanov ◽  
Michiel Wels ◽  
Marjo Starrenburg ◽  
Johan E. T. van Hylckama Vlieg ◽  
Roland J. Siezen ◽  
...  
Keyword(s):  
Genotype Calling ◽  
Calling Algorithm

scholarly journals iCall: a genotype-calling algorithm for rare, low-frequency and common variants on the Illumina exome array

2014 ◽  
Vol 30 (12) ◽  
pp. 1714-1720 ◽  
Author(s):  
Jin Zhou ◽  
Erwin Tantoso ◽  
Lai-Ping Wong ◽  
Rick Twee-Hee Ong ◽  
Jin-Xin Bei ◽  
...  
Keyword(s):  
Low Frequency ◽  
Common Variants ◽  
Genotype Calling ◽  
Calling Algorithm

scholarly journals GEL: a novel genotype calling algorithm using empirical likelihood

2006 ◽  
Vol 22 (16) ◽  
pp. 1942-1947 ◽  
Author(s):  
D. L. Nicolae ◽  
X. Wu ◽  
K. Miyake ◽  
N. J. Cox
Keyword(s):  
Empirical Likelihood ◽  
Genotype Calling ◽  
Calling Algorithm ◽  
Novel Genotype

SNiPer 500K: A Novel SNP Genotype Calling Algorithm

2006 ◽  
Author(s):  
Jianping Hua ◽  
David W. Craig ◽  
Marcel Brun ◽  
Jennifer Webster ◽  
Victoria Zismann ◽  
...  
Keyword(s):  
Genotype Calling ◽  
Calling Algorithm ◽  
Novel Snp

A NEW GENOTYPE CALLING METHOD FOR AFFYMETRIX SNP ARRAYS

2011 ◽  
Vol 09 (06) ◽  
pp. 715-728 ◽  
Author(s):  
BILIN FU ◽  
JIN XU
Keyword(s):  
Linear Model ◽  
Confidence Score ◽  
Small Sample ◽  
Training Data ◽  
Nucleotide Polymorphisms ◽  
Hapmap Data ◽  
Genotype Calling ◽  
Training Scheme ◽  
New Genotype ◽  
Calling Algorithm

Current genotype-calling methods such as Robust Linear Model with Mahalanobis Distance Classifier (RLMM) and Corrected Robust Linear Model with Maximum Likelihood Classification (CRLMM) provide accurate calling results for Affymetrix Single Nucleotide Polymorphisms (SNP) chips. However, these methods are computationally expensive as they employ preprocess procedures, including chip data normalization and other sophisticated statistical techniques. In the small sample case the accuracy rate may drop significantly. We develop a new genotype calling method for Affymetrix 100 k and 500 k SNP chips. A two-stage classification scheme is proposed to obtain a fast genotype calling algorithm. The first stage uses unsupervised classification to quickly discriminate genotypes with high accuracy for the majority of the SNPs. And the second stage employs a supervised classification method to incorporate allele frequency information either from the HapMap data or from a self-training scheme. Confidence score is provided for every genotype call. The overall performance is shown to be comparable to that of CRLMM as verified by the known gold standard HapMap data and is superior in small sample cases. The new algorithm is computationally simple and standalone in the sense that a self-training scheme can be used without employing any other training data. A package implementing the calling algorithm is freely available at .

scholarly journals Variability in GWAS analysis: the impact of genotype calling algorithm inconsistencies

2010 ◽  
Vol 10 (4) ◽  
pp. 324-335 ◽  
Author(s):  
K Miclaus ◽  
M Chierici ◽  
C Lambert ◽  
L Zhang ◽  
S Vega ◽  
...  
Keyword(s):  
Genotype Calling ◽  
Gwas Analysis ◽  
Calling Algorithm ◽  
The Impact

scholarly journals A genotype calling algorithm for affymetrix SNP arrays

2005 ◽  
Vol 22 (1) ◽  
pp. 7-12 ◽  
Author(s):  
N. Rabbee ◽  
T. P. Speed
Keyword(s):  
Genotype Calling ◽  
Snp Arrays ◽  
Calling Algorithm

scholarly journals A genotype calling algorithm for the Illumina BeadArray platform

2007 ◽  
Vol 23 (20) ◽  
pp. 2741-2746 ◽  
Author(s):  
Y. Y. Teo ◽  
M. Inouye ◽  
K. S. Small ◽  
R. Gwilliam ◽  
P. Deloukas ◽  
...  
Keyword(s):  
Genotype Calling ◽  
Calling Algorithm
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