Simulation based benchmarking of isoform quantification in single-cell RNA-seq
| Autor: | Anne C. Ferguson-Smith, Martin Hemberg, Marcela Sjöberg Herrera, Jennifer Westoby |
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| Rok vydání: | 2018 |
| Předmět: |
Gene isoform
0303 health sciences education.field_of_study genetic processes Cell Population RNA-Seq Benchmarking Computational biology Biology 03 medical and health sciences 0302 clinical medicine medicine.anatomical_structure Simulated data medicine natural sciences education Gene Simulation based 030217 neurology & neurosurgery 030304 developmental biology |
| DOI: | 10.1101/248716 |
| Popis: | Single-cell RNA-seq has the potential to facilitate isoform quantification as the confounding factor of a mixed population of cells is eliminated. We carried out a benchmark for five popular isoform quantification tools. Performance was generally good when run on simulated data based on SMARTer and SMART-seq2 data, but was poor for simulated Drop-seq data. Importantly, the reduction in performance for single-cell RNA-seq compared with bulk RNA-seq was small. An important biological insight comes from our analysis of real data which showed that genes that express two isoforms in bulk RNA-seq predominantly express one or neither isoform in individual cells. |
| Databáze: | OpenAIRE |
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