FITdb, an integrated Functional Immunogenomics and Transcriptomics database
6 affiliations
- 1La Jolla Institute for Immunology , La Jolla, CA 92037 ,
- 2Department of Medicine, University of California San Diego , La Jolla, CA 92093 ,
- 3Bioinformatics and Systems Biology Program, University of California San Diego , La Jolla, CA 92093 ,
- 4Department of Molecular Biology, University of California San Diego , La Jolla, CA 92093 ,
- 5Allen Institute for Immunology , Seattle, WA 98109 ,
- 6Department of Pharmacology, University of California San Diego , La Jolla, CA 92093 ,
Abstract
Genetic screens in immune cells enable the systematic interrogation of gene function at scale, uncovering key regulators of cell functions such as tumor cell killing and persistence. However, existing datasets typically focus on specific biological questions, employ targeted gene panels, are generated under diverse experimental conditions, and are not readily accessible, which together limit their integration and future usability. To address this, we developed the Functional Immunogenomics and Transcriptomics database (FITdb), a freely accessible resource that harmonizes functional genomics datasets for the study of immune cell biology. FITdb currently integrates 43 independent functional genetics screens, including 31 bulk and 12 single-cell screens, spanning 20 696 mouse genes and 22 293 human genes across 199 immune cell types and cell states across 29 conditions. Datasets are reanalyzed using a standardized workflow to facilitate cross-study exploration. FITdb provides intuitive, gene-centric visualizations, detailed exploration of individual screens, and access to single-guide RNA-level data. Additionally, built-in tools such as “Compare MyGeneSet” and “Compare MyScreen” identify statistically significant overlaps between user-defined gene lists and functional gene sets in FITdb, and enable direct comparison of user-generated screening data with existing datasets, respectively. Together, FITdb provides a curated, continuously expanding, and user-friendly platform for accelerating the discovery of immune regulatory programs. The database is freely available at https://fitdb.lji.org.
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BibTeX
@article{cen2026fitdb,
title = {{FITdb, an integrated Functional Immunogenomics and Transcriptomics database}},
author = {Xinjian Cen and Qixuan Ma and Kevin Kim and Susanne Gamas-Vis and Ananda Goldrath and Maximilian Heeg and Miguel Reina-Campos},
journal = {Nucleic Acids Research},
year = {2026},
month = oct,
doi = {10.1093/nar/gkag1031},
url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1031/8986446},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - FITdb, an integrated Functional Immunogenomics and Transcriptomics database
AU - Xinjian Cen
AU - Qixuan Ma
AU - Kevin Kim
AU - Susanne Gamas-Vis
AU - Ananda Goldrath
AU - Maximilian Heeg
AU - Miguel Reina-Campos
PY - 2026
DA - 2026/10/23
JO - Nucleic Acids Research
DO - 10.1093/nar/gkag1031
UR - https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1031/8986446
AB - Genetic screens in immune cells enable the systematic interrogation of gene function at scale, uncovering key regulators of cell functions such as tumor cell killing and persistence. However, existing datasets typically focus on specific biological questions, employ targeted gene panels, are generated under diverse experimental conditions, and are not readily accessible, which together limit their integration and future usability. To address this, we developed the Functional Immunogenomics and Transcriptomics database (FITdb), a freely accessible resource that harmonizes functional genomics datasets for the study of immune cell biology. FITdb currently integrates 43 independent functional genetics screens, including 31 bulk and 12 single-cell screens, spanning 20 696 mouse genes and 22 293 human genes across 199 immune cell types and cell states across 29 conditions. Datasets are reanalyzed using a standardized workflow to facilitate cross-study exploration. FITdb provides intuitive, gene-centric visualizations, detailed exploration of individual screens, and access to single-guide RNA-level data. Additionally, built-in tools such as “Compare MyGeneSet” and “Compare MyScreen” identify statistically significant overlaps between user-defined gene lists and functional gene sets in FITdb, and enable direct comparison of user-generated screening data with existing datasets, respectively. Together, FITdb provides a curated, continuously expanding, and user-friendly platform for accelerating the discovery of immune regulatory programs. The database is freely available at https://fitdb.lji.org.
SN - 0305-1048
SN - 1362-4962
ER -