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Introduction to Transcriptomics 

Transcriptomics is the study of all of the transcripts produced by a single cell, individual or population. It has gained much traction since the creation of RNA-Seq, a Next-Generation sequencing method that allows for high-throughput analysis of transcripts. But the question remains: how can we benefit as researchers from studying RNA and transcripts that we couldn't from looking at the DNA level? 

Why Transcripts? 

There was a time when scientists believed that anything that didn't code for a protein was junk. This misbelief meant that we only cared about transcripts that were being translated into proteins. Over time, researchers began to realize that non-coding regions of the genome were not junk, and held significant and biologically functional roles. For example, we now know introns play vital roles in gene regulation, so if we disregard all of the non-protein coding regions, we are missing out on a lot of relevant information.

Because of this newfound belief, science has a seen a substantial increase in many researchers harnessing the powers of Next-Generation Sequencing, especially RNA-Seq.

Transcriptomic Software and Tools

So we already mentioned that RNA-Seq is one of the primary methods to finding out all of the RNA that a particular cell or tissue. But, you'll need some downstream pipeline or software tool ready to be able to process all the information produced by it. We've compiled a list of software that can be used when studying transcriptomics. 

RNA-Seq by Expectation Maximization:  RSEM is a software package that allows the users to find expression level information about transcripts, present within their genomic data. If you're using RNA-Seq data, there's a pipeline available that allows for simultaneous genomic alignment of your data, and expression information. Once the pipeline is run, RSEM will output how much transcriptional expression each transcript has, and gives you valuable visualization tools based on your data as well. 

Trinity RNA-Seq: Trinity is a transcriptome assembly and annotation software package. It allows for de novo transcriptome assembly based on RNA-Seq data. Some of the downstream analysis that it provides include: 

  • Quantifying the abundance of genes and transcripts 
  • Checking the quality of samples and replicates
  • Conducting differential gene expression analysis. 

VennBLAST: VennBLAST is a transcriptome tool that allows for transcriptome visualization comparison across samples. The researchers who created VennBLAST refer to it as a downstream transcriptome tool. Specifically, they state the following: 


VennBLAST provides a birds-eye view of the evolutionary relatedness of whole-transcriptomes, but also enables the dissection of genes into meaningful subgroups which can then be further analyzed using various tools. 


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