Decidual-tissue resident memory T cells protect against nonprimary human cytomegalovirus infection at the maternal-fetal interface
RNA-seq (gene expression) · human · 64 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 64 samples: 32 conditions, mostly in duplicateGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- Decidual-tissue-resident memory T cells protect against nonprimary human cytomegalovirus infection at the maternal-fetal interfaceCell reports · 2024
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE240976_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1005972 and SRA study SRP455369. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 64 samples.
How we read this: 32 replicated groups read from 64 sample titles; they account for 64 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM7713238 w2_mock_neg_rep1 w2_mock_neg
- GSM7713239 w2_mock_neg_rep2 w2_mock_neg
- GSM7713240 w2_cmv_neg_rep1 w2_cmv_neg
- GSM7713241 w2_cmv_neg_rep2 w2_cmv_neg
- GSM7713242 w5_mock_neg_rep1 w5_mock_neg
- GSM7713243 w5_mock_neg_rep2 w5_mock_neg
- GSM7713244 w5_cmv_neg_rep1 w5_cmv_neg
- GSM7713245 w5_cmv_neg_rep2 w5_cmv_neg
- GSM7713246 w9_mock_neg_rep1 w9_mock_neg
- GSM7713247 w9_mock_neg_rep2 w9_mock_neg
- GSM7713248 w9_cmv_neg_rep1 w9_cmv_neg
- GSM7713249 w9_cmv_neg_rep2 w9_cmv_neg
- GSM7713250 w12_mock_neg_rep1 w12_mock_neg
- GSM7713251 w12_mock_neg_rep2 w12_mock_neg
- GSM7713252 w12_cmv_neg_rep1 w12_cmv_neg
- GSM7713253 w12_cmv_neg_rep2 w12_cmv_neg
- GSM7713254 w4_mock_pos_rep1 w4_mock_pos
- GSM7713255 w4_mock_pos_rep2 w4_mock_pos
- GSM7713256 w4_cmv_pos_rep1 w4_cmv_pos
- GSM7713257 w4_cmv_pos_rep2 w4_cmv_pos
- GSM7713258 w6_mock_pos_rep1 w6_mock_pos
- GSM7713259 w6_mock_pos_rep2 w6_mock_pos
- GSM7713260 w6_cmv_pos_rep1 w6_cmv_pos
- GSM7713261 w6_cmv_pos_rep2 w6_cmv_pos
- GSM7713262 w8_mock_pos_rep1 w8_mock_pos
- GSM7713263 w8_mock_pos_rep2 w8_mock_pos
- GSM7713264 w8_cmv_pos_rep1 w8_cmv_pos
- GSM7713265 w8_cmv_pos_rep2 w8_cmv_pos
- GSM7713266 w13_mock_pos_rep1 w13_mock_pos
- GSM7713267 w13_mock_pos_rep2 w13_mock_pos
- GSM7713268 w13_cmv_pos_rep1 w13_cmv_pos
- GSM7713269 w13_cmv_pos_rep2 w13_cmv_pos
- GSM7713270 t1_cmv_rep2 t1_cmv
- GSM7713271 t1_cmv_rep3 t1_cmv
- GSM7713272 t1_mock_rep2 t1_mock
- GSM7713273 t1_mock_rep3 t1_mock
- GSM7713274 t2_cmv_rep2 t2_cmv
- GSM7713275 t2_cmv_rep3 t2_cmv
- GSM7713276 t2_mock_rep2 t2_mock
- GSM7713277 t2_mock_rep3 t2_mock
+ 24 more — browse all 64 samples with per-sample file links →
- GSE330178 Phenotypically similar but functionally distinct NK cell populations within the human maternal-fetal interface 35 samples shares maternal-fetal, interface
- GSE298146 SOX4 Mediated Differentiation of Specific T Lymphocyte Subsets at the Maternal-Fetal Interface Contributes to Preterm Labor [RNA-Seq] 34 samples shares maternal-fetal, interface
- GSE183338 Impaired cell interactions at the pre-eclamptic maternal-fetal interface 22 samples shares maternal-fetal, interface
- GSE330176 Phenotypically similar but functionally distinct NK cell populations within the human maternal-fetal interface [bulkRNA-seq] 20 samples shares maternal-fetal, interface
- GSE298278 Interleukin-27 is antiviral at the maternal-fetal interface 18 samples shares maternal-fetal, interface
- GSE319493 Phenotypically similar but functionally distinct NK cell populations within the human maternal-fetal interface [scRNA-seq] 15 samples shares maternal-fetal, interface
- GSE298153 SOX4 Mediated Differentiation of Specific T Lymphocyte Subsets at the Maternal-Fetal Interface Contributes to Preterm Labor 16 samples shares maternal-fetal, interface
- GSE266854 Viral and host network analysis of the human cytomegalovirus transcriptome in latency 143 samples shares cytomegalovirus
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.