Roderic Guigó

TL;DR: A growing number of in silico cell type deconvolution methods and associated reference panels with cell type–specific marker genes enable the robust estimation of the enrichment of specific cell types from bulk tissue gene expression data.

TL;DR: The results show that the accuracy of GeneID predictions compares currently with that of other existing tools but that GeneID is likely to be more efficient in terms of speed and memory usage.

TL;DR: This unit describes the usage of geneid, an efficient gene-finding program that allows for the analysis of large genomic sequences, including whole mammalian chromosomes, which can be partially annotated and used to refine this initial annotation.

TL;DR: This approach takes into account the complete set of genes known to be involved in disease and suggests that, contrary to current assumptions, many mutations causing disease may actually be affecting the splicing pattern of the genes.

TL;DR: The GENCODE project annotates human and mouse genes and transcripts supported by experimental data with high accuracy, providing a foundational resource that supports genome biology and clinical genomics as mentioned in this paper. But the annotation process does not support the creation of transcript structures and the determination of their function.