Altered TE-derived genes leads to pathogenesis of FXD [PacBioRNASeq]
RNA-seq (gene expression) · human · 84 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
- 84 samples: 84 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
- C G composition in transposon-derived genes is increased in FXD with perturbed immune systemNAR molecular medicine · 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 GSE264089_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 PRJNA1100964 and SRA study SRP502149. 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 84 sample titles: 84 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.
- GSM8210167 TAS1_total, replicate 1_Male FXD
- GSM8210168 TAS1_total,replicate 2_Male FXD
- GSM8210169 TAS2_total, replicate 1_Fale FXD
- GSM8210170 TAS2_total, replicate 2_Fale FXD
- GSM8210171 TAS10_total, replicate 1_Male Healthy
- GSM8210172 TAS10_total, replicate 2_Male Healthy
- GSM8210173 TAS11_total, replicate 1_Female Healthy
- GSM8210174 TAS11_total, replicate 2_Female Healthy
- GSM8210175 TAS18_total, replicate 1_Male FXD
- GSM8210176 TAS18_total, replicate 2_Male FXD
- GSM8210177 TAS19_total, replicate 1_Fale FXD
- GSM8210178 TAS19_total, replicate 2_Fale FXD
- GSM8210179 TAS20_total,replicate 1_Male FXD
- GSM8210180 TAS20_total, replicate 2_Male FXD
- GSM8210181 TAS21_total, replicate 1_Fale FXD
- GSM8210182 TAS21_total, replicate 2_Fale FXD
- GSM8210183 TAS22_total, replicate 1_Female Healthy
- GSM8210184 TAS22_total, replicate 2_Female Healthy
- GSM8210185 TAS23_total, replicate 1_Male Healthy
- GSM8210186 TAS23_total, replicate 2_Male Healthy
- GSM8210187 TAS29_total, replicate 1_Fale FXD
- GSM8210188 TAS29_total, replicate 2_Fale FXD
- GSM8210189 TAS30_total, replicate 1_Female Healthy
- GSM8210190 TAS30_total, replicate 2_Female Healthy
- GSM8210191 TAS36_total, replicate 1_Male FXD
- GSM8210192 TAS36_total, replicate 2_Male FXD
- GSM8210193 TAS39_total, replicate 1_Male FXD
- GSM8210194 TAS39_total, replicate 2_Male FXD
- GSM8210195 TAS41_total, replicate 1_Male Healthy
- GSM8210196 TAS41_total, replicate 2_Male Healthy
- GSM8210197 TAS42_total, replicate 1_Male Healthy
- GSM8210198 TAS42_total, replicate 2_Male Healthy
- GSM8210199 TAS43_total, replicate 1_Female Healthy
- GSM8210200 TAS43_total, replicate 2_Female Healthy
- GSM8210201 TAS48_total, replicate 1_Male ALL
- GSM8210202 TAS48_total, replicate 2_Male ALL
- GSM8210203 TAS49_total, replicate 1_Female ALL
- GSM8210204 TAS49_total, replicate 2_Female ALL
- GSM8210205 TAS50_total, replicate 1_Female ALL-Lymphosarcoma
- GSM8210206 TAS50_total, replicate 2_Female ALL-Lymphosarcoma
+ 44 more — browse all 84 samples with per-sample file links →
- GSE264091 Altered TE-derived genes leads to pathogenesis of FXD 147 samples shares fxd, pathogenesis, te-derived, altered, leads
- GSE264090 Altered TE-derived genes leads to pathogenesis of FXD [ShortReadRNASeq] 63 samples shares fxd, pathogenesis, te-derived, altered, leads
- GSE283315 Investigation of the Altered Transcriptomic Dynamics of Bone Marrow Adipose Tissue Under Exogenous Stimuli in the Context of AML Pathogenesis 36 samples shares pathogenesis, altered
- GSE221740 Plasma multi-omics identify early pathogenesis and biomarkers of SCD post-AMI 106 samples shares pathogenesis
- GSE261775 A systems-biology approach connects aging mechanisms with Alzheimer’s disease pathogenesis [TCPY] 94 samples shares pathogenesis
- GSE292317 CYP1B1-AS1 regulates CYP1B1 to promote Coxiella burnetii pathogenesis by inhibiting ROS and host cell death 78 samples shares pathogenesis
- GSE275765 Neuronal Activity-Dependent Gene Dysregulation inC9orf72i3Neuronal Models of ALS/FTD Pathogenesis 78 samples shares pathogenesis
- GSE272035 Gene community-regulated pathway analysis successfully deciphers pathogenesis and biomarkers of viral versus metabolic hepatocellular carcinoma 71 samples shares pathogenesis
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.