Aligning RNA seq data to genome or transcriptome
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5.2 years ago
KVC_bioinfo ▴ 550

Hello,

I am trying to understand the pros and cons of aligning RNA-seq data to reference genome or transcriptome. Can anyone help me understand it? Also, does that also affect the choice aligners for analysis?

RNA-Seq ngs transcriptome genome • 8.4k views
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It depends on your purpose and kind of data you have and quality of genome/transcriptome references available.

For example, for differential expression analysis of known genes/transcripts, pseudo-mapping (or quasi-aligning) to the transcriptome is much faster and demands less memory, with the same level of accuracy as quantifying after aligning to the genome.

But if you want to call variants with RNAseq data, it is better to align to the genome, to avoid reads aligning to spurious locations on the transcriptome.

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I am dealing with RNA-Seq data and aligning with human transcriptome. I am interested in looking the expression of viral elements in breast cancer RNAseq data and study the differentially expressed gene.

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Please do not use # with tags.

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If the genome is model genome, in RNA-seq, the mainstream is to map to the transcriptome, which can great help to guide the splice site identification.