Illuminating the dark side of the human transcriptome with long read transcript sequencing.
Richard I KuoYuanyuan ChengRunxuan ZhangJohn W S BrownJacqueline SmithAlan L ArchibaldDavid W BurtPublished in: BMC genomics (2020)
Long read transcript sequencing data has the power to identify novel genes within the highly annotated human genome. The use of parameter tuning and extensive output information of the TAMA software package allows for in depth exploration of eukaryotic transcriptomes. We have found long read data based evidence for thousands of unannotated genes within the human genome. More development in sequencing library preparation and data processing are required for differentiating sequencing noise from real genes in long read RNA sequencing data.
Keyphrases
- single cell
- rna seq
- genome wide
- endothelial cells
- electronic health record
- single molecule
- induced pluripotent stem cells
- pluripotent stem cells
- data analysis
- dna methylation
- gene expression
- healthcare
- computed tomography
- bioinformatics analysis
- air pollution
- transcription factor
- mass spectrometry
- social media
- health information
- deep learning
- optical coherence tomography
- genome wide analysis
- contrast enhanced
- artificial intelligence
- tandem mass spectrometry