# Data Management and Analysis Core

> **NIH NIH U19** · LA JOLLA INSTITUTE FOR IMMUNOLOGY · 2022 · $173,311

## Abstract

Project Summary
 The Data Management and Analysis Core (DMAC) will continue to provide centralized data management
and analysis services for the LJI HIPC center projects and cores, as it has successfully done since the inception
of the HIPC Program at LJI in 2015. Further, the DMAC will ensure the ongoing timely submission of data and
data analyses obtained under this award to the ImmPort database and other repositories identified by NIAID.
 For centralized data management, we will utilize our in-house, data management system of
interconnected databases and analysis scripts. This is centered around the Donor Record Administration System
(DoRAS) for tracking donors and samples along with clinical information. Here we will extend DoRAS to ensure
that all clinical information relevant to the present proposal can be captured. The database will be accessible
through the internet and provide a consistent basis to select samples and interpret results. All information in
DoRAS is de-identified, so that research projects will not have access to sensitive information, allowing data to
be freely shared.
 In terms of data analysis services, the DMAC will build on the procedures established successfully in the
last 6 years and provide a set of automated analysis pipelines that take data generated in each Project and
provide standardized analyses that will facilitate inter-project comparisons and reproducibility. Pipelines for bulk
RNA-seq have already been fully implemented including user friendly web reports for the generated results.
Initial pipelines for single-cell- RNA-seq analysis have been established, and will continue to be optimized. For
high-dimensional cytometry analysis as generated by flow or mass-cytometry, we will be using a combination
of traditional manual gating approaches and directed automated gating methods, in particularly Directed
Automated Filtering and Identification of cell populations (DAFI)1, which was developed in the previous funding
period. Also, we will optimize and automate a TCR-seq analysis pipeline that will identify TCRs in various
experimental settings. Power calculations will also be provided.
 To facilitate efficient data sharing with ImmPort, and to follow guidelines for data standards set by the
newly introduced HIPC Coordinating Center (HCC), we will take advantage of the fact that the data generated
through automated pipelines in this proposal is already in a standardized format, and ties back to the sample
and human subject information captured in DoRAS. Updates to data standards are easily implemented in these
pipelines, and will generate the desired export format for ImmPort, GEO or SRA. Additionally, DMAC will provide
dedicated staff with experience in data submissions to ensure that study specific data elements not covered by
the automated pipelines will be appropriately submitted. We have extensive experience and success with this
approach, as evidenced by our track record of submissions in the last funding p...

## Key facts

- **NIH application ID:** 10419456
- **Project number:** 2U19AI118626-08
- **Recipient organization:** LA JOLLA INSTITUTE FOR IMMUNOLOGY
- **Principal Investigator:** Bjoern Peters
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $173,311
- **Award type:** 2
- **Project period:** 2015-06-15 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10419456

## Citation

> US National Institutes of Health, RePORTER application 10419456, Data Management and Analysis Core (2U19AI118626-08). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10419456. Licensed CC0.

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