The hgvs package requires sequence data and exon structures to map variants between the genome and transcript coordinates, to infer protein sequence changes from transcripts and to validate variants.
Differences between the reference genome and transcript libraries complicate the determination of the effect of genomic sequence variants on protein products; similarly, these differences complicate the mapping of sequence variants found in transcripts to their respective genomic position.
For both steps, it is imperative to consider conflicts between the reference genome and transcript libraries.
The correlation coefficient of the case-control ratio of the 215 differentially expressed genes between genome- and transcript-aligned reads was 0.73 and between transcript-aligned reads and array hybridization was 0.46 (data not shown).
Only 25 genes were common to both alignments, but 96% of the 215 had congruent direction of change and correlation between genome- and transcript-aligned fold-change was 0.73.
Edited RNA sites for transcripts of cox1, cob, and cox3 were investigated using comparisons between assembled genomes and transcripts.
(A complete overview can be found in the online bioinformatic databases of genome and transcripts, protein structure, and brain expression).
the transcript alignment validation procedure can verify perfect sequence matches between the genome and the transcript sequence at n-number of bp adjoining the tentative splice junction (default for n is three bp, as employed here).
While we may miss some alignments involving rare non-standard introns or some Agilent cDNA clones due to our algorithm, we maintain a high stringency of matches between genome coordinates, probes, and transcripts.
To quantify this phenomenon, we performed a partial correlation analysis by calculating the correlation between genome-wide transcript abundance prediction residuals for TF and HM+DNase models [ 42].
