Sex-biased genes in chicken have a larger variance in expression level, are expressed in fewer tissues, and at lower overall levels than unbiased genes.
RNA-Seq data is inherently heteroskedastic in that abundantly expressed genes have greater variance in expression than low abundance genes.
The score can be further adjusted for highly expressed genes which takes into account the level of variance in expression across all tissues in order to reduce the contention of highly ubiquitously expressed housekeeping genes.
The large variance in expression between genes reflects the fact that some genes are highly expressed in all tissues, and others genes are expressed at low levels.
The literature reports a wide variance in expression of EGFR protein in primary tumours and metastases, ranging from <10% to almost 100%.
Gender-fluid people simply take this day-to-day and moment-to-moment variance in expression we see in cisgender people, and expand upon it.
TSRs are constructed in such a way that the first TSR explains the largest amount of variance in expression and each subsequent TSR explains the largest amount of the remaining variance in expression while remaining uncorrelated with previously constructed TSRs.
In this specific two-species dataset the first PC (PC1) explained ∼25% of the total variance in expression.
Similar results were observed in mice where 50 TSRs explained 71% of the variance in expression of 9,062 genes in 3,934 arrays (Fig. 1A).
Furthermore, we selected for clustering the smallest set of genes with the greatest variance in expression (variance filter in TMEV program) that showed the most robust cluster result with the highest support from the bootstrap analysis.
