Modeling and cleaning RNA-seq data significantly improve detection of differentially expressed genes.
Igor V DeynekoOrkhan N MustafaevAlexander А TyurinKsenya V ZhukovaAlexander VarzariIrina V Goldenkova-PavlovaPublished in: BMC bioinformatics (2022)
Application of RNAdeNoise to our RNA-seq data on polysome profiling and several published RNA-seq datasets reveals its suitability for different organisms and sequencing technologies such as Illumina and BGI, shows improved detection of differentially expressed genes, and excludes the subjective setting of thresholds for minimal RNA counts. The program, RNA-seq data, resulted gene lists and examples of use are in the supplementary data and at https://github.com/Deyneko/RNAdeNoise .
Keyphrases
- rna seq
- single cell
- electronic health record
- big data
- genome wide
- randomized controlled trial
- gene expression
- dna methylation
- systematic review
- multidrug resistant
- quality improvement
- physical activity
- depressive symptoms
- loop mediated isothermal amplification
- label free
- artificial intelligence
- real time pcr
- bioinformatics analysis
- nucleic acid