kallisto, bustools, and kb-python for quantifying bulk, single-cell, and single-nucleus RNA-seq.

Area of Science:

• Molecular Biology
• Bioinformatics
• Genomics

Background:

• RNA sequencing (RNA-seq) is crucial for quantifying RNA species in biological samples.
• Existing methods require efficient and accessible computational tools for data analysis.
• Distinguishing between nascent and mature RNA is vital for understanding gene regulation.

Approach:

• This protocol utilizes the free, open-source software suite: kallisto, bustools, and kb-python.
• The workflow preprocesses raw RNA-seq reads to generate gene expression quantifications.
• The method supports analysis of bulk tissue, single cells, and single nuclei.

Key Points:

• The kallisto, bustools, and kb-python pipeline provides a comprehensive solution for RNA-seq data preprocessing.
• Gene expression can be quantified at the individual cell or sample level.
• The protocol facilitates the classification of RNA species into nascent and mature forms.

Conclusions:

• This detailed protocol enables researchers to effectively preprocess RNA-seq data using accessible bioinformatics tools.
• The described workflow enhances the ability to perform accurate gene expression analysis across diverse experimental designs.
• The software suite supports advanced applications, including the study of RNA dynamics in single cells and nuclei.