SAIL engineers create software that helps researchers understand mechanisms underlying cancer

BY GINA MANTICA

Different types of cells in the body such as skin cells and eye cells are made by turning different sets of genes “on” or “off”. With state-of-the-art technologies like single cell RNA-sequencing (scRNA-seq), researchers can now study the diversity of genes turned on or off in different cell types to better understand the underlying mechanisms of diseases like cancer. Until now, however, there wasn’t one robust tool that could verify the quality of the data collected through scRNA-seq.

Engineers at the Hariri Institute’s Software & Application Innovation Lab (SAIL) helped Junior Faculty Fellow Joshua Campbell and Steering Committee member Evan Johnson create The Single Cell ToolKit (SCTK), enabling researchers to run multiple quality control algorithms for scRNA-seq data in one place. The results were published recently in Nature Communications.

“Through a joint effort between SAIL and students in the Bioinformatics program, we created a comprehensive and easy-to-use quality control workflow for the Human Tumor Atlas Network, an initiative that uses single cell technologies to characterize cancer cells,” says Campbell, an Assistant Professor in Computational Biomedicine at the BU Department of Medicine. This workflow can be run on cloud platforms such as Terra or Seven Bridges.

Prior to the creation of SCTK, researchers didn’t have one software package that could run through a comprehensive set of quality control tools for scRNA-seq. “To assess and exclude low-quality cells before downstream analysis, you’d need to separately download, install, and run each tool,” explains Campbell, “which can be tedious and time-consuming”. He wanted to create code that can import scRNA-seq data from multiple formats, run a bunch of quality control tools, and visualize the results all in one place.

The platform, enabled by SAIL, supports data in 11 file formats from different preprocessing tools. “SAIL transformed the beta SCTK into a user interface accessible to a wider audience. This was a true collaboration where the SCTK tool had functionality that needed to be translated to a Graphical User Interface (GUI),” says Jeff Simeon, Associate Director of Programs & Product Management at SAIL. SAIL designed these interfaces with input from Campbell’s team.

SCTK conducts a comprehensive quality control analysis and produces standardized reports and simple visualizations to assess scRNA-seq data efficiently. The simplicity and robust nature of the platform allows for greater reproducibility by computational biomedical researchers.

People without any programming experience whatsoever can use this platform online at sctk.bu.edu, says Campbell.  SCTK enables more researchers without computational backgrounds to analyze scRNA-seq data and study the diversity of genes turned on or off in different types of cells from the same tissue. This tool is an important step in a larger pipeline to efficiently analyze the diversity of cells in the human body, driving progress towards the treatment of cancers.

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