35 research outputs found

    Comparison in haplotype frequency estimation between PCLM and PHASE (left panel), and PCLM and EM (right panel).

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    <p>Top panels: linear scales, bottom panels: logarithmic (base 10) scales. The red lines represent equality.</p

    Graph of AIC as a function of for controls (left) and cases (right).

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    <p>Graph of AIC as a function of for controls (left) and cases (right).</p

    An illustration of tomato AFLP markers.

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    <p>The color bar at the right shows the coding of the fuzzy genotypes. In addition, in the truly fuzzy genotypes a yellow cross has been plotted.</p

    Estimated linkage disequilibrium for all markers on tomato chromosome 9, as measured by .

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    <p>Estimated linkage disequilibrium for all markers on tomato chromosome 9, as measured by .</p

    Estimated probabilities and error bars for 32 haplotypes of 5 SNPs in cases (right panel) and controls (left panel) in the cervical carcinoma data.

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    <p>The small squares show the prior probabilities . Haplotypes and numerical values of probabilities are shown to the left in each panel.</p

    Comparison in haplotype frequency estimation between “fuzzy” PCLM (left panel), and “crisp” PCLM (right panel) in logarithmic (base 10) scales.

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    <p>The red lines represent equality. The “crisp” PCLM shows the results by not correctly handling genotype uncertainty.</p

    Estimated linkage disequilibrium for all markers on tomato chromosome 9, as measured by .

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    <p>Estimated linkage disequilibrium for all markers on tomato chromosome 9, as measured by .</p

    How to quantify information loss due to phase ambiguity in haplotype case-control studies-0

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    <p><b>Copyright information:</b></p><p>Taken from "How to quantify information loss due to phase ambiguity in haplotype case-control studies"</p><p></p><p>BMC Genetics 2005;6(Suppl 1):S108-S108.</p><p>Published online 30 Dec 2005</p><p>PMCID:PMC1866831.</p><p></p>es 1/1 and 2/2, 'H' a heterozygote 1/2. (2) The y-label is ordered by A-optimality (the highest 'HHH' group for the first selection, the 'H1H', 'HH1', etc), the red points by D-optimality. So the first individuals to be selected are 'H1H' group, not 'HHH', and hence it shows discrepancy using two different measures. The jumps between groups indicate the correlation between parameters

    Total Plasma N‑Glycome Changes during Pregnancy

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    During pregnancy, the mother faces a major immunological challenge. Most of the major plasma proteins have important immunological functions, and altered levels of these major proteins have been reported during pregnancy, potentially providing immunosuppression. A large number of the high abundance plasma proteins are post-translationally modified by N-glycans, and while it is now understood that these glycans may also affect the immunological functions, their pattern has not been studied in relation to pregnancy. Here, the N-glycosylation profile of 32 pregnant women was determined over the course of their pregnancy using a multiplexed CGE-LIF method. Moreover, for 6 women, the glycosylation profiles of the proteins IgG, IgA, and alpha1-antitrypsin were monitored. For total plasma, 16 glycan signals showed differential expression during pregnancy. In general the levels of largely sialylated bi-, tri-, and tetra-antennary glycans were increased during pregnancy, while biantennary glycans with no more than one sialic acid were decreased. Similarly altered glycosylation profiles were observed for the individual proteins IgG, with a decrease of digalactosylated biantennary glycans after delivery, and alpha1-antitrypsin, on which increased levels of triantennary glycans were observed during pregnancy. Overall, these results show altered glycosylation profiles both for total plasma glycoproteins and on individual proteins during pregnancy, which may contribute to immunosuppression and have other biological functions
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