Supplemental Material for Newman et al., 2018

Comparison of Event analysis with RSEM to Event Analysis with eXpress and these approaches to transcript estimation with iRecko

Haplotype risk analysis of WTCCC type 1 diabetes data.

<p>We assessed the risk of haplotypes spanning <i>HLA-DRB1</i>, <i>HLA-DQA1</i> and <i>HLA-DQB1</i>, and compared these to the published risk estimates from an independent study <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064683#pone.0064683-Cucca1" target="_blank">[20]</a>. The published odds ratios were based on transmission/non-transmission of alleles from familial data, while our odds ratios were estimated from case/control data. We used the same classification scheme by dividing haplotypes into three risk groups. The odds ratios are computed with respect to the DRB1*01-DQA1*0101-DQB1*0501 haplotype.</p

Correlation between imputed and typed dosages (<i>r</i>²_dosage) of classical HLA alleles in the B58BC as a function of typed allele frequency for imputation from the (a) Affymetrix 500 K or (b) Illumina Immunochip platform using the HapMap-CEPH reference panel, and imputation from the (c) Affymetrix 500 K or (d) Illumina Immunochip platform using the T1DGC reference panel.

<p>Black points indicate 2-digit HLA alleles. Red points indicate 4-digit HLA alleles.</p

Overview of the HapMap-CEPH and T1DGC reference panels and the B58BC validation panel.

<p>The MHC region is defined here as 29–34 Mb on chr6 (hg17). Sample size is based on unrelated (founder) individuals. The number of unique 4-digit classical HLA alleles at each locus is shown for each data set. Intragenic SNPs, amino acids, and indels represent unique polymorphic positions as defined by the classical HLA types in each data set.</p

Overview of the SNP2HLA imputation procedure.

<p>The reference panel (top) contains SNPs in the MHC, classical HLA alleles at the class I and class II loci, and amino acid sequences corresponding to the 4-digit HLA types at each locus. For a data set with genotyped SNPs across the MHC (bottom), we use the reference panel to impute classical alleles and their corresponding amino acid polymorphisms.</p

Correlation between imputed and typed dosages (<i>r</i>²_dosage) of polymorphic amino acids in the B58BC as a function of typed allele frequency for imputation from the (a) Affymetrix 500 K or (b) Illumina Immunochip platform using the HapMap-CEPH reference panel, and imputation from the (c) Affymetrix 500 K or (d) Illumina Immunochip platform using the T1DGC reference panel.

<p>Black points indicate bi-allelic positions. Red points indicate poly-allelic positions.</p

Imputation accuracy measured as the genotype concordance for two- and four-digit classical HLA alleles measured in the British 1958 Birth Cohort (B58BC, 918 individuals) as a function of reference panel (HapMap or T1DGC) and genotyping platform (in B58BC).

<p>Comparisons were made only if both alleles were typed at the same resolution (two- or four-digit). Accuracy was based on the same set of variants, allowing a direct and fair comparison between reference panels and genotyping platforms.</p

Association analysis of WTCCC type 1 diabetes data.

<p>We imputed classical HLA alleles and polymorphic amino acids in 1,963 cases and 2,939 controls using the T1DGC reference panel, and tested all variants for association with logistic regression. Of all variants tested, the top hit maps to amino acid position 57 in HLA-DQβ1, consistent with a previous study <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064683#pone.0064683-Todd1" target="_blank">[16]</a>.</p

Imputation accuracy of classical alleles at 4-digit resolution across worldwide populations.

<p>Imputations were performed using the T1DGC reference panel, and accuracy (as measured by genotype concordance) in the three HapMap panels (CEU/CEPH, YRI and CHB+JPT) with the publicly available gold-standard HLA genotype data <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064683#pone.0064683-deBakker1" target="_blank">[8]</a>. Accuracy is consistently high across all loci in Europeans (CEU/CEPH), but much worse in the African (YRI) and East-Asian (CHB+JPT) populations.</p