21 research outputs found

    The number of detected <i>cis</i>-eQTLs is dependent on the expression levels of the transcripts.

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    <p>(A) Quantile-normalized average expression intensity and (B) number of <i>cis</i>-eQTL affected probes in percentage, for 2,140 lincRNA probes, 2,140 non-lincRNA (matched for 2,140 lincRNA probes' median expression and standard deviation) and 2,140 most abundantly expressed non-lincRNA probes.</p

    Distribution of lincRNA <i>cis</i>-eQTLs with respect to different transcripts.

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    <p>(A) The majority of the lincRNA <i>cis</i>-eQTLs are located within the non-coding part of the genome and less than 6% of lincRNA <i>cis</i>-eQTLs are located within mRNA. (B) Distribution of lincRNA <i>cis</i>-eQTLs with respect to distance to the lincRNA transcripts. The x-axis displays the 250 kb window used for <i>cis</i>-eQTL mapping and the y-axis displays the fraction of lincRNA <i>cis</i>-eQTLs located within this window.</p

    Analytical “bake-off” of whole genome sequencing quality for the Genome Russia project using a small cohort for autoimmune hepatitis

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    <div><p>A comparative analysis of whole genome sequencing (WGS) and genotype calling was initiated for ten human genome samples sequenced by St. Petersburg State University Peterhof Sequencing Center and by three commercial sequencing centers outside of Russia. The sequence quality, efficiency of DNA variant and genotype calling were compared with each other and with DNA microarrays for each of ten study subjects. We assessed calling of SNPs, indels, copy number variation, and the speed of WGS throughput promised. Twenty separate QC analyses showed high similarities among the sequence quality and called genotypes. The ten genomes tested by the centers included eight American patients afflicted with autoimmune hepatitis (AIH), plus one case’s unaffected parents, in a prelude to discovering genetic influences in this rare disease of unknown etiology. The detailed internal replication and parallel analyses allowed the observation of two of eight AIH cases carrying a rare allele genotype for a previously described AIH-associated gene (<i>FTCD</i>), plus multiple occurrences of known <i>HLA-DRB1</i> alleles associated with AIH <i>(HLA-DRB1-03</i>:<i>01</i>:<i>01</i>, <i>13</i>:<i>01</i>:<i>01 and 7</i>:<i>01</i>:<i>01</i>). We also list putative SNVs in other genes as suggestive in AIH influence.</p></div

    Genotype comparison.

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    <p>(A) Concordance of WGS genotypes with microarray genotypes. The concordance was estimated based on the trio data as the ratio of microarray SNPs with identical genotypes in WGS results. (B) Comparison of the three WGS datasets between each other in terms of precision, sensitivity and F-measure for pairwise comparisons. Color legend is given on the top right. (C) Concordance of genotypes in the three WGS datasets for all variants, SNPs and indels. Color legend is given on the top right.</p

    The number of <i>cis-</i>regulated tags per gene.

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    <p>The percentages of cis-regulated tags mapping into the same gene are indicated (781 genes overall). For nearly half of the genes (48%) only one tag shows an eQTL effect. If multiple tags map within the same gene, only one eQTL tag should pass the FDR<0.05 significance threshold while the other tag could be less significant. For these eQTLs the allelic direction is shown: same allelic direction (multiple tags within the same gene are cis-regulated by a SNP in the same direction), significantly opposite allelic direction (multiple tags within the same gene are cis-regulated by a SNP but with opposite directions and the difference between the correlation coefficients is significant), or opposite allelic direction but not significant (if the difference between correlation coefficients is not significant).</p
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