A maximum likelihood method for detecting bad samples from illumina beadchips data

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Nội dung chi tiết: A maximum likelihood method for detecting bad samples from illumina beadchips data

A maximum likelihood method for detecting bad samples from illumina beadchips data

Table of ContentsOverview11Introduction31.1Biological background ....................................... 31.2Sonic common types of mutation ..........

A maximum likelihood method for detecting bad samples from illumina beadchips data ..................... 51.3SNP and SNP genotype......................................... 61.4Microarray technology and Illumina Beadchips..............

... 71.5Genotype callers ............................................ 81.6Quality control and quality assurance........................ 91.6.1Identify A maximum likelihood method for detecting bad samples from illumina beadchips data

samples with discordant sex information .... 101.6.2Identify samples that have high missing and heterozygosity rate 111.6.3Identify duplicated or rel

A maximum likelihood method for detecting bad samples from illumina beadchips data

ated samples............... 111.6.1Identify samples that have different ancestries...... 122Genotype callers142.1llluminus............................

Table of ContentsOverview11Introduction31.1Biological background ....................................... 31.2Sonic common types of mutation ..........

A maximum likelihood method for detecting bad samples from illumina beadchips data ..... 182.1Coinparing three callers.................................... 183Maximum likelihood method for detecting bad samples203.1Create potent ial h

ad sample list............................213.2Estimate the fitness of data.................................223.3Remove bad samples................... A maximum likelihood method for detecting bad samples from illumina beadchips data

.......................2-14Experimental result254.1Input file format ...........................................254.2Experiment 1.....................

A maximum likelihood method for detecting bad samples from illumina beadchips data

............................27List of Figures1.1DMA structure.................................................. 41.2Human genome, chromosome and genes

Table of ContentsOverview11Introduction31.1Biological background ....................................... 31.2Sonic common types of mutation ..........

A maximum likelihood method for detecting bad samples from illumina beadchips data ......................152.2x.y intensities vs. strength and contrast [T1S+O7]............ 173.1The workflow of the method.............................

........214.1VCP file format example?.......................................261.2SNP rs2465126 before ami after removingbad samples............281.3SN A maximum likelihood method for detecting bad samples from illumina beadchips data

P rs2488991 before ami after removingbad samples............294.4SNP rs6055460 before and after removingbad samples............32iii

Table of ContentsOverview11Introduction31.1Biological background ....................................... 31.2Sonic common types of mutation ..........