# Turning a sequence barcode into a spectral barcode for single-cell analysis.

> **NIH NIH R21** · UNIVERSITY OF TEXAS AT AUSTIN · 2020 · $181,900

## Abstract

Project Summary:
The use of sequence barcodes has enabled high-throughput transcriptomic analysis of single cells. But one
challenge remains – there is no method to map the physical assessments of single cells and the downstream
transcriptomic data of single cells to the same cells of origin. This is because currently sequence barcodes are
only read by sequencing which takes place after all single cells are lysed, reverse transcription is completed,
and cDNA are amplified and pooled. In order to perform transcriptomic analysis and physical assessments on
the same single cells, we will need a method that allows us to decipher the sequence barcodes while in the
process of single-cell physical interrogation. Our goal in this proposed research is to develop a new method to
turn sequence barcodes into spectral barcodes that can be read locally in the process. The proposed sequence-
barcode-reading technique, if it can be realized, will have substantial impact to the single-cell community as it
will become the only method to map the physical assessments and the downstream molecular analysis data to
the same cells of origin in a high-throughput, streamlined format.

## Key facts

- **NIH application ID:** 9898410
- **Project number:** 5R21GM129617-02
- **Recipient organization:** UNIVERSITY OF TEXAS AT AUSTIN
- **Principal Investigator:** ILYA J FINKELSTEIN
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $181,900
- **Award type:** 5
- **Project period:** 2019-04-01 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9898410

## Citation

> US National Institutes of Health, RePORTER application 9898410, Turning a sequence barcode into a spectral barcode for single-cell analysis. (5R21GM129617-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9898410. Licensed CC0.

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