# Immune repertoire sequencing: error correction, analysis, and visualization on the cloud

> **NIH NIH R43** · DIGITAL PROTEOMICS LLC · 2020 · $217,313

## Abstract

Project Summary
 Antibodies are vital molecules produced by the adaptive immune system, and are a
critical component in identifying foreign agents for removal within an organism. Produced by B
cells, antibodies have an enormously diverse set of possible compositions, created by somatic
recombination and hypermutation processes that are specific to these types of immune cells.
Due to their incredible diversity, studying them for the purpose of antibody discovery or disease
characterization, becomes a difficult task.
 Recently, next-generation sequencing (NGS) technologies have been successfully
applied to study the diverse repertoire of antibodies produced by B cells. This technology has
proven incredible for understanding this component of the immune response in a new level of
detail. Unfortunately, NGS produced strings contain errors as part of the process. These errors
can be confused as true sequence diversity, and can confound downstream analysis and
interpretation. Furthermore, structuring such deep sequenced antibody repertoire data for
answering questions about the immune response is non-trivial and compute resource intensive;
problems that not many labs are well suited to address.
 Our proposal seeks to break down barriers for entry of these repertoire sequencing
assays by providing innovative informatics approaches to error correction and analysis,
delivering results in an interactive cloud platform. Our service will be the first to offer
non-human/mouse species support, as well as support for transgenic animals, critical for many
drug discovery companies.

## Key facts

- **NIH application ID:** 10010744
- **Project number:** 1R43GM137688-01
- **Recipient organization:** DIGITAL PROTEOMICS LLC
- **Principal Investigator:** Natalie Castellana
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $217,313
- **Award type:** 1
- **Project period:** 2020-04-01 → 2021-05-10

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10010744

## Citation

> US National Institutes of Health, RePORTER application 10010744, Immune repertoire sequencing: error correction, analysis, and visualization on the cloud (1R43GM137688-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10010744. Licensed CC0.

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