F1000Research F1000Research 2046-1402 F1000 Research Limited London, UK 10.12688/f1000research.162267.1 Research Article Articles A curated collection of transcriptome datasets to study the transcriptional response in blood and nasal samples following viral respiratory inoculation and vaccination

[version 1; peer review: 1 approved with reservations]

 Lan Zheng Data Curation Validation https://orcid.org/0000-0002-7439-110X 1 Zhang Tongli Data Curation Writing – Original Draft Preparation 2 Zhang Yu Resources 1 Sun Xuejun Resources 1 Liu Chuwen Resources 1 Liu Pei Resources 3 Tang Muyao Formal Analysis Visualization 1 Fu Meng Visualization 1 Hagood James S. Resources https://orcid.org/0000-0003-3938-0330 4 5 Pickles Raymond J Resources 5 6 Zou Fei Conceptualization Investigation Supervision a 1 Zheng Xiaojing Conceptualization Investigation Methodology Supervision Writing – Review & Editing b 1 7 Department of Biostatistics, The University of North Carolina at Chapel Hill Department of Biostatistics, Chapel Hill, North Carolina, USA Industrial Engineering & Operations Research Department, University of California Berkeley, Berkeley, California, USA Department of Probability and Statistics, University of Science and Technology of China, Hefei, Anhui, China Department of Pediatrics, Division of Pulmonology, UNC School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA Marsico Lung Institute, UNC School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA Department of Microbiology & Immunology, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA Department of Pediatrics, Division of Infectious Diseases, UNC School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA feizou@email.unc.edu xiaojinz@email.unc.edu

No competing interests were disclosed.

 13 5 2025 2025 14 493 3 4 2025 Copyright: © 2025 Lan Z et al. 2025 This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background

Our understanding of the human immune system’s response to viral respiratory tract infections (VRTIs) and vaccines, including the molecular mechanisms and correlates of protection, remains incomplete. Extensive transcriptomic data from inoculation and vaccination studies have been deposited in publicly available databases. However, these studies are often separate and difficult to locate.

 Methods

To bridge this research gap, we have systematically searched and reviewed publicly available datasets from NCBI Gene Expression Omnibus (GEO), Archive of Functional Genomics Data (ArrayExpress), Immunology Database and Analysis Portal (ImmPort), and Google using targeted queries. Inoculation study queries included terms related to humans, blood, PBMCs, nasal, respiratory challenges, and respiratory viral inoculations; while vaccination study queries focused on humans, blood, PBMCs, transcriptomes, and respiratory viral vaccines or vaccinations.

 Results

This collection includes 18 datasets from inoculation of 5 respiratory viruses: H1N1, H3N2, RSV, HRV, and SARS-CoV-2 (14 from blood and 4 from nasal swabs) with 429 participants (ages 18 to 55 years) and 37 datasets from vaccination of influenza and COVID-19 with 2,084 participants (ages 0.5 to over 89 years). The duration and number of post-immunization time points range from 14 days before to 28 days after inoculation (1 to 20 time points) and from 28 days before to 360 days after vaccination (1 to 13 time points).

 Conclusion

We provide a curated compendium of public gene expression data repositories for researchers to reanalyze transcriptomes from human whole blood, peripheral blood mononuclear cells (PBMCs), and nasal swab samples. This will facilitate studies of transcriptional responses to respiratory viral inoculation or vaccination.

 Transcriptomics Bioinformatics Vaccination Inoculation Respiratory viral infection Influenza viruses COVID Respiratory syncytial viruses (RSV) Human rhinoviruses (HRV) Whole Blood PBMC. This work is supported by National Institute of Allergy and Infectious Diseases (NIAID) of the National Institutes of Health (NIH) P01AI178377 National Heart Lung and Blood Institute(NHLBI) of the NIH R01HL173044 This work is supported by National Institute of Allergy and Infectious Diseases (NIAID) of the National Institutes of Health (NIH) under grant [P01 AI178377]; National Heart Lung and Blood Institute(NHLBI) of the NIH under grant [R01 HL173044] Introduction

Viral respiratory tract infections (VRTIs) are widespread globally, causing significant illnesses and hospitalizations each year. 1 The importance of studying VRTIs has grown in light of the global COVID-19 pandemic. 2 VRTIs involve a range of viruses, including respiratory syncytial viruses (RSV), human rhinoviruses (HRV), and influenza and coronaviruses. 3 Most VRTIs lack both effective antiviral therapies and approved vaccines. 4

In-depth investigation of human immune responses to inoculation and vaccination is critically needed. To facilitate further research, we have compiled a curated dataset collection, which includes transcriptomic data from the blood and nasal swabs of volunteers who underwent inoculation and vaccination, specifically for influenza, COVID-19, RSV, and HRV.

Our curated dataset collection is divided into two categories: inoculation studies and vaccination studies. The inoculation collection includes 18 datasets with 429 participants, while the vaccination collection comprises 37 datasets with 2,084 participants. All datasets were sourced from GEO, ImmPort Shared Data, and the ArrayExpress Collection at EMBL-EBI. 5– 7 These datasets have been organized into a publicly accessible format for download and further analysis.

 Methods

The datasets were gathered using specific search queries across GEO, ArrayExpress, ImmPort, and Google search. The queries for inoculation studies included terms related to humans, blood, PBMCs, nasal, respiratory challenges, and viral inoculations. The vaccination study queries followed similar criteria, focusing on humans, blood, PBMCs, transcriptomes, and vaccines or vaccinations. The search queries used for GEO, ArrayExpress, and Google search to find inoculation studies are as follows:

GEO and ArrayExpress Inoculation Search Query

(“humans”[MeSH Terms] OR “Homo sapiens”[Organism] OR Homo sapiens [All Fields]) AND ((“blood”[Subheading] OR “blood”[MeSH Terms] OR blood [All Fields]) OR PBMC [All Fields] OR PBMCs [All Fields]) AND respiratory [All Fields] AND (challenge [All Fields] OR “experimentally infected”[All Fields] OR inoculated [All Fields])

 Google Inoculation Search Query

Homo sapiens AND (blood OR PBMC OR PBMCs) AND transcriptome AND respiratory AND (inoculation OR challenge OR “experimentally infected” OR inoculated)

The search queries used for GEO, ArrayExpress, and Google to find vaccination studies are as follows:

 GEO and ArrayExpress Vaccine Search Query

(“humans”[MeSH Terms] OR “Homo sapiens”[Organism] OR Homo sapiens [All Fields]) AND ((“blood”[Subheading] OR “blood”[MeSH Terms] OR blood [All Fields]) OR PBMC [All Fields] OR PBMCs [All Fields]) AND respiratory [All Fields] AND ((“vaccination”[MeSH Terms] OR inoculation [All Fields]) OR (“vaccines”[MeSH Terms] OR vaccine [All Fields]) OR (“vaccines”[MeSH Terms] OR vaccines [All Fields]) OR (“vaccination”[MeSH Terms] OR vaccination [All Fields]))

 Google Vaccine Search Query

Homo sapiens AND (blood OR PBMC OR PBMCs) AND transcriptome AND respiratory AND (vaccine OR vaccines OR vaccination)

For ImmPort, vaccine studies were located using the following filters:

Species: Homo sapiens

Research Focus: Vaccine Response

Condition or Disease: COVID-19 AND Influenza

Results

The majority of datasets obtained were derived from human blood, PBMCs, and nasal swabs, generated using Illumina or Affymetrix platforms or through RNA sequencing. Every dataset identified through this search was carefully curated manually. This involved thoroughly reviewing the dataset descriptions, examining the study designs, and reading through the related original articles on PubMed. Ultimately, we only included studies that involved human whole blood, PBMCs, and nasal swabs linked to VRTI inoculation or vaccination for our dataset collection. According to these criteria, we retained 18 inoculation datasets and 37 vaccine-related datasets.

The data selection process for inoculation is summarized in Figure 1a. Using GEO and ArrayExpress inoculation query, 108 studies were found with Homo sapiens as the primary organism. Google search returned 92 inoculation studies. The data selection process for vaccination is summarized in Figure 1b. GEO and ArrayExpress Vaccine query identified 82 studies where Homo sapiens is the top organism. Google search produced 89 vaccination studies. ImmPort search yielded 99 vaccination studies.

Flowchart illustrating construction of inoculation (a) and vaccination (b) dataset compendium.

Figure 2 illustrates the distribution of participants over time in 18 inoculation studies, involving 429 participants aged 18 to 55 years, across five respiratory viruses: H1N1, H3N2, RSV, HRV, and SARS-CoV-2. There is a notable peak on day 0. The duration and number of post-immunization time points range from 14 days before to 28 days after inoculation, spanning 1 to 20 time points. Notably, 56 participants from four studies had both blood and nasal samples, and they were counted separately. Subsequent time points show smaller but consistent sample collections, with varying contributions from different pathogens. H1N1, H3N2, and HRV are the most frequently sampled pathogens, while SARS-CoV-2 and RSV contribute fewer samples to the dataset.

A collection of datasets covering transcriptional responses to inoculation over time across varying viruses.

Histogram of the time points pre- and post-inoculation available in our compendium. Each virus is indicated by a different color. The height of the bars represents the number of participants with available gene expression data.

Figure 3 summarizes the distribution of 2,084 participants, aged 0.5 to over 89 years, over time in 37 vaccination studies covering COVID-19 and influenza vaccines and their types. The peak occurred on day 0, with participant recruitment enriched during the first week. The duration and number of post-immunization time points range from 28 days before to 360 days after vaccination, spanning 1 to 13 time points.

A collection of datasets covering transcriptional responses to vaccination over time across COVID-19 and influenza.

Histogram of the time points pre- and post-vaccination is available in our compendium. Each vaccine and type are indicated by a different color. The height of the bars represents the number of participants with available gene expression data.

The complete list of inoculation datasets included in our collection can be found in Table 1.

Complete list of inoculation datasets.
Pathogen Sample type Sample size Profiling platform Time point Accession number Citation
HRV Peripheral blood 50 Microarray (Affymetrix) -0.88, 0, 0.21, 0.5, 0.88, 1.21, 1.5, 1.88, 2.21, 2.5, 2.88, 3.21, 3.5, 3.88, 4.21, 4.5, 4.92, 5.21, 5.92, 6.92 GSE73072 8
RSV 20
H3N2 38
H1N1 43
HRV Peripheral blood 20 Microarray (Affymetrix) 0 GSE17156 9
RSV 20
H3N2 17
H3N2 Peripheral blood 17 Microarray (Affymetrix) 0, 0.21, 0.50, 0.88, 1.21, 1.50, 1.88, 2.21, 2.50, 2.88, 3.21, 3.50, 3.88, 4.21, 4.50 GSE30550 10
H3N2 Whole blood 11 Microarray (Illumina) 0,0.50,1,2 GSE61754 11
SARS-CoV-2 Blood and nose swabs 36 RNA-seq 0, 0.25, 14, 28(blood) 0,1,3,5,7,10,14(nose swabs) E-MTAB-12993 12
H3N2 Blood and nose swabs 20 RNA-seq 0, 1, 2, 3, 7, 10, 14, and 28(blood) 0,1, 2,3,7,14(nose swabs) EGAD50000000956
HRV Nose swabs 17 Microarray (Affymetrix) -14,0.33, 2.00 GSE11348 13
H1N1 Whole blood 21 Microarray (Illumina) 0, 1, 2, 3, 4 GSE90732 14
RSV Nose swabs 58 RNA-seq 0,3 GSE155237 15
H1N1 PBMC 24 Microarray (Affymetrix) 0, 0.21, 0.50, 0.90, 1.21, 1.50, 1.90, 2.21, 2.50, 2.90, 3.21, 3.50, 3.90, 4.21, 4.50 GSE52428 16
H3N2 17

PBMC: peripheral blood mononuclear cells.

Time point: Unit is day. 0 is the baseline, negative number means days before inoculation, and positive means days after inoculation.

Accession number: datasets from GEO start with “GSE”, datasets from ArrayExpress start with “E-MTAB”, dataset from EGA starts with “EGAD”.

We have collected transcriptomes from 18 cohorts across 10 inoculation studies, totaling 429 participants. This collection covers inoculations of five respiratory viruses: H1N1, H3N2, RSV, HRV, and SARS-CoV-2. The time span ranges from -14 to 28 days before and post for inoculation. The sample source includes blood (n=14) and nasal swabs (n=4). The transcriptomic data types include microarrays from Illumina (n=2) and Affy (n=11); bulk RNA-seq (n=5) ( Figure 4).

Distribution of inoculation datasets across different profiling platforms.

The complete list of vaccination datasets included in our collection can be found in Table 2.

Complete list of vaccine datasets.
Pathogen Vaccine type Sample type Sample size Profiling platform Time point Accession number Citation
Influenza TIV PBMC 172 Microarray (Illumina) 0,2,7,28 GSE107990 17
Influenza LAIV Whole blood 20 Microarray (Illumina) 0,1,7,30 GSE52005 18
Influenza TIV Whole blood 17 Microarray (Illumina) 0,1,7,30
Influenza LAIV PBMC 28 Microarray (Affymetrix) 0,3,7 GSE29619 19
Influenza TIV PBMC 28 Microarray (Affymetrix) 0,3,7
Influenza LAIV and inactivated Blood 44 RNA-seq 0,3,7,29,85,92,113 GSE217770 20
Influenza inactivated PBMC 50 RNA-seq 0,1,3,7,21,22,24,28 GSE102012 21
Influenza LAIV Nasal epithelium 40 RNA-seq 0,3 GSE230494 22
Influenza LAIV Nasal cells 55 RNA-seq 0,5,12 GSE117580 23
Influenza TIV Nasal cells 62 RNA-seq 0,5,12
Influenza vetor viral virus Whole blood 11 Microarray (Illumina) 0,0.5,1,2 GSE61754 11
Influenza Inactivated PBMC 14 RNA-seq -7,0,1,2,3,4,5,6,7,8,9,10,21 GSE45764 24
Influenza Inactivated Whole blood 18 Microarray (Illumina) -7,0,1,3,7,10,14,21,28 GSE30101/GSE48762 25
Influenza Inactivated PBMC 212 Microarray (Affymetrix) 0,3,7,14 GSE74817 26
Influenza Inactivated Whole blood 247 Microarray (Illumina) 0,1,3,14 GSE48024
Influenza Inactivated Whole blood 91 Microarray (Illumina) 0 GSE41080
Influenza Inactivated PBMC 5 RNA-seq 0,1,2,3,4,5,6,7,8,9,10 GSE45735
Influenza Inactivated PBMC 60 Microarray (Illumina) 0,2,4,7,28 GSE59743/GSE95584
Influenza Inactivated PBMC 27 Microarray (Affymetrix) 0,3,7 GSE29617/GSE29614
Influenza Inactivated PBMC 64 Microarray (Illumina) 0,2,4,7,28 GSE59654
Influenza Inactivated Whole blood 51 Microarray (Illumina) 0,2,7,28 GSE101709
Influenza Inactivated PBMC 42 Microarray (Illumina) 0,4,7,28 GSE59635
Influenza Inactivated Whole blood 44 Microarray (Illumina) 0,2,7,28 GSE101710
Influenza Inactivated PBMC 63 Microarray (Affymetrix) -7,0,1,7,70 GSE47353
Influenza LAIV PBMC 28 Microarray (Affymetrix) 0,3,7 GSE29615
influenza Inactivated Whole blood 123 Microarray (Affymetrix) −7,0,1,3,7,10,14,21,28 SDY311/SDY312/SDY314/SDY315/SDY112 27
Influenza TIV Whole blood 34 Microarray (Illumina) 0,7,14 SDY272/SDY648/SDY739/SDY819/SDY622 28
influenza TIV Whole blood 65 RNA-seq 0,2,7,28 SDY1393 29
Influenza TIV Whole blood 6 RNA-seq 1,3,60 SDY300 *
COVID mRNA PBMC 16 scRNA 0,7,21,28 GSE247917 30
COVID mRNA Blood 23 RNA-seq 0,1,2,3,4,5,6,7,8,9 GSE190001 31
COVID mRNA PBMC 214 RNA-seq 0,22,90,180,360 GSE220682 32
COVID mRNA Blood 6 scRNA 0,1,2,7,21,22,28,42 GSE171964 33
COVID mRNA Blood 56 RNA-seq 0,1,7,21,22,28 GSE169159
COVID mRNA PBMC 8 scRNA 28,35,60,110,201 GSE195673 34
COVID mRNA PBMC 4 scRNA 0,7,30,90 GSE210229 35
COVID vetor viral virus Whole blood 36 RNA-seq 0,50,57 GSE228842 36

PBMC: peripheral blood mononuclear cells; LAIV: live attenuated influenza vaccine; TIV: trivalent inactivated influenza vaccine.

Time point: Unit is day. 0 is the baseline, negative number means days before vaccination, and positive means days after vaccination.

Accession number: datasets from GEO start with “GSE”, datasets from ImmPort start with “SDY”.

This data is available at ImmPort ( https://immport.org/shared/home) under study accession SDY300: Healthy Human DC and monocyte subsets transcriptional regulations in response to Fluzone 2010-2011 and pneumococcal vaccinations.

We have gathered transcriptomes from 37 cohorts across 22 vaccine studies, totaling 2084 participants. This collection focuses on studying Influenza and COVID-19 vaccines. The time span ranges from -28 to 360 days. The data source includes blood (n=34) and nasal swabs (n=3). The transcriptomic data types include microarrays from Illumina (n=13) and Affy (n=7); bulk RNA-seq (n=13) and scRNA-seq (n=4) ( Figure 5). Vaccine types: TIV (n=22) and LAIV (n=6) were used for influenza vaccination, mRNA vaccine (n=7) was used for COVID-19 vaccination, and vector adenovirus (n=2) was used for both influenza and COVID-19, one of each.

Distribution of vaccine datasets across different profiling platforms. Ethics and consent

Ethical approval and consent were not required.

 Data availability

All datasets in our curated collection are also accessible to the public on the NCBI GEO website at https://www.ncbi.nlm.nih.gov/gds/ ArrayExpress at https://www.ebi.ac.uk/biostudies/arrayexpress/studies ImmPort at https://www.immport.org/shared/home, and the European Genome-phenome Archive (EGA) 37 at https://ega-archive.org/datasets/ cited in the manuscript using its GEO number, ArrayExpress number, ImmPort study number or EGA study number. All these citation and accession numbers are listed in Table 1. The dataset can be found by searching for the accession number on the corresponding websites listed above. Note that downloading from ImmPort requires registering a personal account on their website.

 Accession number

NCBI: Expression Omnibus (GEO): Transcriptome datasets of the transcriptional response in blood samples following HRV, RSV, H3N2 and H1N1 inoculation. Accession Number: GSE73072; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE73072 8

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets of the transcriptional response in blood samples following HRV, RSV and H3N2 inoculation. Accession Number: GSE17156; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17156 9

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets of the transcriptional response in blood samples following H3N2 inoculation. Accession Number: GSE30550; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE30550 10

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets of the transcriptional response in blood samples following H3N2 inoculation. Accession Number: GSE61754; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE61754 11

EMBL-EBI: ArrayExpress: Transcriptome datasets of the transcriptional response in blood and nasal samples following SARS-CoV-2 inoculation. Accession Number: E-MTAB-12993; https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-12993 12

European Genome-Phenome Archive (EGA): Transcriptome datasets to study the transcriptional response in blood samples following H3N2 inoculation. Accession Number: EGAD50000000956; https://ega-archive.org/datasets/EGAD50000000956 12 (Data available on request)

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in nasal samples following HRV inoculation. Accession Number: GSE11348; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11348 14

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following H1N1 inoculation. Accession Number: GSE90732; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE90732 15

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in nasal samples following RSV inoculation. Accession Number: GSE155237; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE155237 15

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following H1N1 and H3N2 inoculation. Accession Number: GSE52428; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE52428 16

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE107990; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107990 17

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE52005; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE52005 18

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE29619; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE29619 19

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE217770; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE217770 20

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE102012; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE102012 21

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in nasal samples following influenza vaccination. Accession Number: GSE230494; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE230494 22

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in nasal samples following influenza vaccination. Accession Number: GSE117580; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE117580 23

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE61754; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE61754 11

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE45764; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE45764 24

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE30101 and GSE48762; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE30101 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48762 25

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE74817; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE74817 26

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE48024; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48024 26

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE41080; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE41080 26

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE45735; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE45735 26

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE59743 and GSE95584; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE59743 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE95584 26

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE29617 and GSE29614; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE29617 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE29614 26

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE59654; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE59654 26

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE101709; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE101709 26

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE59635; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE59635 26

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE101710; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE101710 26

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE47353; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE47353 26

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: GSE29615; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE29615 26

ImmPort: Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: SDY311, SDY312, SDY314, SDY315 and SDY112; https://www.immport.org/shared/study/SDY311, https://www.immport.org/shared/study/SDY312, https://www.immport.org/shared/study/SDY314, https://www.immport.org/shared/study/SDY315 and https://www.immport.org/shared/study/SDY112 27

ImmPort: Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: SDY272, SDY648, SDY739, SDY819 and SDY622; https://www.immport.org/shared/study/SDY272, https://www.immport.org/shared/study/SDY648, https://www.immport.org/shared/study/SDY739, https://www.immport.org/shared/study/SDY819 and https://www.immport.org/shared/study/SDY622 28

ImmPort: Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: SDY1393; https://www.immport.org/shared/study/SDY1393 29

ImmPort: Transcriptome datasets to study the transcriptional response in blood samples following influenza vaccination. Accession Number: SDY300; https://www.immport.org/shared/study/SDY300

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following COVID vaccination. Accession Number: GSE247917; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE247917 30

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following COVID vaccination. Accession Number: GSE190001; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE190001 31

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following COVID vaccination. Accession Number: GSE220682; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE220682 32

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following COVID vaccination. Accession Number: GSE171964 and GSE169159; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE171964 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE169159 33

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following COVID vaccination. Accession Number: GSE195673; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE195673 34

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following COVID vaccination. Accession Number: GSE210229; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE210229 35

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in blood samples following COVID vaccination. Accession Number: GSE228842; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE228842 36

NCBI: Gene Expression Omnibus (GEO): Transcriptome datasets to study the transcriptional response in nasal samples following HRV inoculation. Accession Number: GSE11348; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11348 13

Acknowledgment

We extend our gratitude to all the researchers who have publicly shared their datasets by depositing them in GEO, ArrayExpress, ImmPort and EGA.

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Genet. 2015;47(7):692–695. 26111507 10.1038/ng.3312 PMC5426533 10.5256/f1000research.178441.r418093 Reviewer response for version 1 Gardinassi Luiz Gustavo 1 Referee https://orcid.org/0000-0002-9027-2688 University of Sao Paulo, Ribeirão Preto, State of São Paulo, Brazil

Competing interests: No competing interests were disclosed.

 29 10 2025 Copyright: © 2025 Gardinassi LG 2025 This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. recommendation approve-with-reservations

The data compendium described in this manuscript can be a useful community resource. There are a few issues that need to be better explored.

- Define inoculation studies as controlled human challenges and the advantages of such experimental approach to understand host transcriptional responses in the introduction section. What are the main differences compared to natural infections? How are they more related to vaccine studies? 

- Although the compendium gathered the studies into the same framework, it is unclear how many studies are ready to be used in statistical and other analysis and those that need additional processing before moving forward to statistical and functional analysis, such as filtering and normalization. This can have a major influence depending on the computational resources from users.

Is the work clearly and accurately presented and does it cite the current literature?

Yes

If applicable, is the statistical analysis and its interpretation appropriate?

Not applicable

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Partly

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

Systems immunology, transcriptomics, metabolomics applied to the study of infectious and parasitic diseases.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.