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The 1% chromosome-wise thresholds for LRT are listed in Additional file 2. The average heritability was of 0.45 ± 0.25 for the 272 transcripts with at least one significant eQTL.

The Benjamini-Hochberg 33 correction for false discovery rate in multiple comparisons was also applied setting the point-wise threshold for the correction at 0.05.

We then set 0.99 quantile of these LRT distributions for each chromosome, as a 1% chromosome-wise threshold for detection of eQTL.

A third QTL was identified on chromosome 10, just below the α = 0.05 genome-wise threshold and significant at the α = 0.10 genome-wise threshold for the joint two-part model LOD score.

Delay-insensitive effects were identified as clusters that showed recollection-related activity for both immediate and delayed lists, each thresholded at p < 0.032 for a joint voxel-wise threshold of p < 0.001, exclusively masking for any significant effect of delay (liberally defined at p < 0.05).

To assess effects of intelligibility on cerebro-acoustic coherence more broadly we conducted a whole-brain search for regions in which coherence was higher for the intelligible 16 channel speech than for the unintelligible 1 channel speech, using a voxel-wise threshold of P < 0.001, corrected for multiple comparisons (P < 0.05) using cluster extent.

We next tested all possible marker and 1 cM marker interval pairs for interactions with experiment-wise threshold of P = 0.05 by 500 permutations [28].

For all group analyses, we applied a voxel-wise threshold of p<0.05 (family wise error corrected) and a minimum cluster size of 10 coherent voxels.

Significance thresholds were determined for each gene-trait combination individually at a comparison-wise threshold of P < 0.05 after 1000 permutations.

For all results, we report clusters with a voxel-wise threshold of P < 0.001 (uncorrected) and cluster-size >3 voxels (81 mm), with additional family-wise error (FWE) correction for multiple comparisons where indicated.

Bonferroni corrections for multiple-testing were used to estimate the genome-wise and chromosome-wise significant thresholds for the GWAS-based analyses.

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