Brotman Baty Institute

Single Cell Sequencing Center

Single Cell Sequencing Platform

The Brotman Baty Advanced Technology Lab offers single cell molecular profiling by “Single cells by Combinatorial Indexing” technologies including sci-RNA-seq. Single cell molecular profiling has revolutionized our ability to understand cell type composition in complex tissues and to uncover which of those cell types are affected by disease. Developed in the lab of Jay Shendure, MD PhD in the Department of Genome Sciences, combinatorial indexing methods have been optimized for production by the Advanced Technology Lab. These powerful single cell sequencing methods have a greatly reduced cost per cell thereby democratizing atlas-scale projects and allowing parallelization of hundreds of samples.

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Pseudotime Dynamics / Branch Module

How Our Single Cell Sequencing Service Works

We now offer a suite of services for single nucleus sequencing and data interpretation. Our tools support multiplexed single nucleus RNA-seq, from nuclei isolation through single cell sequencing and analysis. We employ comprehensive quality control measures at each step, including: quality control of sample input, sample isolation, sci-RNA-seq experiments and analyses. Our bioinformatics pipelines include breakdown of sequence to Cell by Gene by Count matrices, advanced quality control metrics and automated cell typing. See how the single cell sequencing lab can help optimize your efforts.

Thousands to Millions of Nuclei

The sci-RNA-seq method returns thousands of cells per sample making this a key technology for probing tissue complexity and understanding how gene expression and cell-type composition change under different conditions. Sci-RNA-seq experiments scale sublinearly with cost; each full experiment returns hundreds of thousands of nuclei. Investigators can choose to profile from thousands to millions of nuclei. The single cell sequencing team is optimizing isolation and sequencing protocols for a diverse range of samples and experiments. With inputs as low as 0.5 x 10^6 cells or 20mg of tissue, we perform sequencing at scale for many systems.

Optimized Protocols for Various Model Systems

  • Model Organisms (D. melanogaster, C. elegans, D. rerio)
  • Embryonic Mammalian Tissues
  • Adult Mouse Tissues
  • Cell-based systems (cell lines, primary B or T cells, organoids…)
  • Xenografts
  • Other model organisms with STAR alignments and ENSEMBL annotations

Suite of Services

sci-RNA-sequencing

The Advanced Technology Lab is adept at isolating nuclei from a wide range of tissues and cell types. Each scaled sci-RNA-seq experiment includes a diverse set of samples, all loaded as fixed nuclei. The power of the combinatorial indexing approach allows us to combine many experiments into one: we are able to profile large cell atlases as well as tissue- or cell-specific projects. Our experimental service includes experimental consultation, multiple quality control steps, and production level sci-RNA-seq runs.

sci-RNA-seq3 protocol - Cao et al, Nature
Advanced Technology Lab Bioinformatics Dashboard

Data processing pipeline

The Brotman Baty bioinformatics team preprocesses all single cell sequencing data and returns data ready to use, including a web dashboard that shows the results of some basic quality control and analysis. We return all raw data as well as a premade Cell Data Set (cds) object to use with Monocle3 , a well-developed toolkit for analyzing single-cell gene expression experiments. Basic Monocle3 analyses and quality control steps are outlined in the web dashboard, allowing investigators with limited R programming experience to jump right into data analysis.

Fred Hutch Center for Data Visualization

Human survival has always hinged on the ability to translate visual signals into patterns, trends, and correlations. In the age of big data, this aptitude has proven effective at turning data into life-saving discoveries. The Center for Data Visualization combines software, statistics, and science through storytelling to illuminate, inspire, and most importantly, lead to new biologic and therapeutic insights. We aim to develop open-source, web-based tools to assist researchers in the exploration of multi-modal Single Cell experiments.

A single cell transcriptional landscape of mammalian organogenesis.