RNA-Seq Blog Transcriptome Research & Industry News
RNA-SEQ – Mapping to a Reference Genome – by Kevin Libuit
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- Application of Single Cell Sequencing (SCS) Technology
- Researchers use single-cell approaches and deep learning to map all stages of fruit fly embryo development
- DeLTa-Seq – direct-lysate targeted RNA-Seq from crude tissue lysate
- Tumor bulk-RNA seq identifies patients at high risk of progression in non-complete pathological responders from NADIM trial
- STRIDE – a topic-model-based method to deconvolve spatial transcriptomics using scRNA-seq
- Researchers find heart failure arises from mutations in numerous distinct genes
- Transcriptome diversity in human tissues mapped with emerging long-read RNA sequencing technology
- Significance analysis for clustering with single-cell RNA-sequencing data
- BacDrop – droplet-based single-cell RNA-seq reveals heterogeneity in bacterial populations and in response to antibiotic perturbation
- Gruffi – an algorithm for improved delineation of developmental trajectories in organoids and resemblance to in vivo data.
Thanks Kevin. I am new to bioinformatics and just beginning to understand the nuances of data analysis. Although I understand that TopHat aligns split-reads across splice junctions, I need to know which of the MANY aligners are actually better over the others and why?
Even though there might be many tools, I need to know why I should prefer to use a tool and not others. I hope you could shed some light on this difficult question. I work with mouse and human data and need to use spilce-junction reads for the analysis.
Thanks!