bioRxivBioinformaticsPreprint
IG-28 enables identification and quantification of high-confidence isoforms from large bulk and single-cell full-length cDNA datasets
Alessandro CalicchioiD, Amanda O. Li, Tanvi Herwadkar, Honey E. MekoneniD, Christopher VollmersiD
Abstract
The technology to sequence full-length transcriptomes from bulk and single-cell samples has rapidly advanced. As a result, full-length cDNA datasets now reach billions of reads in size which is beyond the capability of most established isoform identification tools. Here, we introduce IG-28 which addresses this challenge with its capability to process and analyze large fl-cDNA datasets fast and using minimal computational resources. In contrast to its predecessor Mandalorion, IG-28 is not limited to bulk fl-cDNA but is capable of parsing, processing, and analyzing single-cell fl-cDNA datasets. It does so in a lightweight, flexible manner, integrating seamlessly with established scRNA-seq analysis workflows. We benchmarked IG-28 against a variety of established and new isoform identification tools using several bulk and a complex single-cell fl-cDNA dataset and found that IG-28 consistently outperformed the other tools by identifying high-confidence public isoforms.
- assay: bulk RNA-seq
- assay: scRNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: variant calling
- approach: statistical model
- Citations
- 0
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