Transcriptomic profiling of kidney transplant recipients [RNA-seq]
RNA-seq (gene expression) · human · 74 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
- 74 samples: 74 samples, each with a distinct title — no replicated groupsGroups 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
- An epigenetic human cytomegalovirus infection score predicts viremia risk in seropositive lung transplant recipientsEpigenetics · 2024
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 GSE250426_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 PRJNA1054044 and SRA study SRP478593. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 74 sample titles: 74 distinct titles with little repetition. 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.
- GSM7978975 Kidney_U1123R_pre (751799_S41)
- GSM7978976 Kidney_1484_pre (751946_S45)
- GSM7978977 Kidney_U1124R_pre (753145_S39)
- GSM7978978 Kidney_1494_pre (753559_S3)
- GSM7978979 Kidney_1489_pre (753984_S13)
- GSM7978980 Kidney_U1132R_pre (754643_S69)
- GSM7978981 Kidney_U1136R_pre (755385_S21)
- GSM7978982 Kidney_1505_pre (756689_S33)
- GSM7978983 Kidney_1501_pre (756760_S47)
- GSM7978984 Kidney_1457_pre (757911_S43)
- GSM7978985 Kidney_U1148R_pre (758557_S29)
- GSM7978986 Kidney_U1143R_pre (760863_S17)
- GSM7978987 Kidney_1468_pre (761070_S7)
- GSM7978988 Kidney_U1146R_pre (761101_S65)
- GSM7978989 Kidney_1508_pre (762191_S37)
- GSM7978990 Kidney_1541_pre (763205_S19)
- GSM7978991 Kidney_1521_pre (763866_S15)
- GSM7978992 Kidney_1512_pre (763915_S67)
- GSM7978993 Kidney_1511_pre (763946_S31)
- GSM7978994 Kidney_1517_pre (764694_S51)
- GSM7978995 Kidney_1515_pre (765367_S49)
- GSM7978996 Kidney_1558_pre (766672_S1)
- GSM7978997 Kidney_1553_pre (766767_S63)
- GSM7978998 Kidney_1523_pre (766943_S72)
- GSM7978999 Kidney_1543_pre (766944_S9)
- GSM7979000 Kidney_1522_pre (767020_S11)
- GSM7979001 Kidney_1527_pre (767196_S57)
- GSM7979002 Kidney_1528_pre (767370_S59)
- GSM7979003 Kidney_1536_pre (767438_S35)
- GSM7979004 Kidney_1535_pre (767726_S73)
- GSM7979005 Kidney_1546_pre (767804_S53)
- GSM7979006 Kidney_1551_pre (767837_S27)
- GSM7979007 Kidney_1547_pre (768075_S55)
- GSM7979008 Kidney_1534_pre (768490_S5)
- GSM7979009 Kidney_U1112R_pre (PRETX12-6_S25)
- GSM7979010 Kidney_1476_pre (PRETX26-6_S61)
- GSM7979011 Kidney_U1111R_pre (PRETX31-6_S23)
- GSM7979012 Kidney_1476_post (R9597-6_S62)
- GSM7979013 Kidney_1484_post (R9653-6_S46)
- GSM7979014 Kidney_1489_post (R9690-6_S14)
+ 34 more — browse all 74 samples with per-sample file links →
- GSE334923 Single-cell RNA-seq atlas of peripheral blood and kidney graft immune cells in chronic antibody-mediated rejection 48 samples shares rna-seq, kidney
- GSE342790 Development-inspired approach for the derivation of functional and transplantable salivary gland organoids from human pluripotent stem cells [RNA-Seq] 16 samples shares transplant, rna-seq
- GSE310058 Single-nucleus transcriptomic profiling of human lung tissue in chronic obstructive pulmonary disease (COPD) [snRNA-seq] 149 samples shares rna-seq
- GSE319641 RNA-Seq profiling of pre- and on-treatment tumor samples from breast cancer patients enrolled in the NeoTRIP trial. 401 samples shares rna-seq
- GSE317207 Transcriptomic profiling of human hepatocellular carcinoma biopsy samples using bulk RNA-seq 33 samples shares rna-seq
- GSE319969 Spatial and Bulk Transcriptomic Profiling Defines the Molecular Evolution of Cutaneous Squamous Cell Carcinoma and Reveals Stage-Specific Biomarkers of Clinical Relevance [RNA-Seq] 24 samples shares rna-seq
- GSE327707 Sorted bulk RNA-seq profiling of human peripheral blood mononuclear cell populations across diverse in vitro immune stimuli 150 samples shares rna-seq
- GSE327167 Single-cell RNA-seq profiling of pleural mesothelioma and comparator pleural specimens 113 samples shares rna-seq
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.