6 research outputs found
Predicted location of the putative mutation causing posterior polymorphous corneal dystrophy on 20p11.23.
<p>Filled triangles show 5% significance level of disease mutation location on chromosome 20 in cM; a 60 kb region between markers D20S182 and M189K21.</p
Geographical origin of families with posterior polymorphous corneal dystrophy within the southwestern part of the Czech Republic.
<p>The geographical origin of the eldest members of each family is indicated by *. Twelve of the families, of which ten were genotyped and shown to share common haplotype, can be traced to a region of 13 km radius around the town of Klatovy. Two other genotyped families with the common full haplotype spanning over 23 Mb originate from an approximate 40 km radius from Klatovy, however knowledge of the place of origin only extended to three generations in both families.</p
Summary of posterior polymorphous corneal dystrophy study families and subjects.
<p>Number of phenotyped and genotyped affected family members, unaffected first degree relatives and spouses included in this study. Presence of shared haplotype across 20p12.1- 20q12 spanning over 23 Mb as well as the core mini-haplotype at 20p12.1-20p11.23 in affected individuals, previous molecular genetic analysis and geographical origin within the Czech Republic of the eldest family member known to be affected is also shown.</p><p>N = No, Y = yes.</p><p>Linkage analysis for families 1 and 2 was reported in Gwilliam <i>et al</i>. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0045495#pone.0045495-Gwilliam1" target="_blank">[11]</a>. Results of previous candidate gene screening in families 15–19 has been reported in Liskova <i>et al</i>. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0045495#pone.0045495-Liskova2" target="_blank">[23]</a>.</p
Estimated age for posterior polymorphous corneal dystrophy linked to 20p12.1-20p11.23 in Czech patients.
<p>Maximum probability represented by 5% significance interval shown as filled triangles was found at 90 generations (range 64 to 133), i.e. 1800 years assuming a 20-year generation time.</p
Overlap of significantly associated rSNPs identified by ASE and GTE.
<p>The percentage of overlapping rSNPs detected by allele-specific expression (ASE) and genotype expression (GTE) analysis is plotted for varying numbers of samples. The top 9536 SNPs from the GTE analysis are compared with the top 38203 SNPs from the ASE analysis, which corresponds to a Bonferroni threshold of p = 0.05 for a GTE sample size of 395 and an ASE sample size of 188. The p-value cut-offs were adapted so that the same SNP top-list sizes were obtained at all sample sizes for both GTE (p-value of 1.17E-7, 1.06E-4, 1.93E-3, 6.12E-3 for n = 395, n = 188, n = 95, and n = 50 respectively) and ASE (p-value of 8.06E-8, 9.35E-5, 4.90E-3 for n = 188, n = 95, and n = 50 respectively). The vertical axes show the percentage of SNPs in the top-lists detected by both GTE and ASE analysis and the horizontal axes show the number of samples analyzed using GTE and ASE, respectively. The percentage overlap is calculated by dividing the number of overlaps with the number of top SNPs in the GTE analysis. In (A), each line shows the effect on the number of overlapping SNPs detected by ASE analysis of a specific sample size when the sample size in GTE analysis was increased. In (B), each line shows the effect on the number of overlapping rSNPs detected by GTE analysis of a specific sample size when the samples size in ASE analysis is increased.</p
The ability of ASE and GTE analysis to detect significantly associated rSNPs at different MAF.
<p>Fractions of rSNPs are shown for different minor allele frequencies (MAF) with significant association signals according to a Bonferroni-corrected p-value of 0.05. Each data point underlying the curves represents the fraction of significant associations within a 1% MAF bin. Sliding 5% MAF window averages are plotted for different sample sizes analyzed by ASE and GTE. Both methods detect a lower fraction of low frequency rSNPs, compared to the fraction of all the SNPs at the same frequency (black line). The ASE method detects a higher fraction of the SNPs (solid lines) with a MAF <15% than GTE (dashed lines) regardless of sample size except for the largest GTE sample set.</p