What is kallisto RNA-seq?

kallisto is a program for quantifying abundances of transcripts from RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads. It is based on the novel idea of pseudoalignment for rapidly determining the compatibility of reads with targets, without the need for alignment.

What is the difference between transcript level versus gene level RNA-seq read counts?

The difference between gene-level and transcript level quantification is, well, that gene-level summarizes counts over genes, and transcrpt-level summarizes counts over transcripts.

What is bootstrap in kallisto?

Kallisto can thus be run either in a single step (which is very fast) or in “bootstrap” mode (which takes longer, but can be done on several processors in parallel) in order to get uncertainty estimates for the expression levels – a kind of error bars for the quantification process.

What is a kallisto index?

Kallisto is a program for quantifying abundances of transcripts from RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads. It is based on the novel idea of pseudoalignment for rapidly determining the compatibility of reads with targets, without the need for alignment.

What is transcript level?

Transcript expression level, refers to how abundant a transcript is, i.e. if a certain mRNA (a transcript) exist in many or few copies (expression level).

How fast is Kallisto’s RNA-Seq technology?

On benchmarks with standard RNA-Seq data, kallisto can quantify 30 million human reads in less than 3 minutes on a Mac desktop computer using only the read sequences and a transcriptome index that itself takes less than 10 minutes to build.

Why is RNA-Seq alignment so difficult?

DOI: 10.1093/bioinformatics/bts635 Abstract Motivation: Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies.

What are the steps involved in RNA-Seq data analysis?

We review all of the major steps in RNA-seq data analysis, including quality control, read alignment, quantification of gene and transcript levels, differential gene expression, functional profiling, and advanced analysis. They will be discussed later. Figure 1. The general workflow of RNA-seq analysis.

Why is Kallisto so fast and accurate?

Pseudoalignment of reads preserves the key information needed for quantification, and kallisto is therefore not only fast, but also as accurate as existing quantification tools.