A Conserved NLRC5 Signaling Pathway in Developing Human Cortical Neurons is Required for Interferon Gamma Driven Changes in HLA Class I Expression and Neural Activity
RNA-seq (gene expression) · human · 15 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
- 15 samples: 15 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.
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 GSE298027_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 PRJNA1267128 and SRA study SRP587355. 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 15 sample titles: 15 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.
- GSM9004963 IFN1-LineD-Dif1-Sample1
- GSM9004964 IFN2-LineC-Dif3-Sample1
- GSM9004965 IFN3-LineD-Dif1-Sample2
- GSM9004966 IFN4-LineD-Dif3-Sample1
- GSM9004967 IFN5-LineC-Dif1-Sample1
- GSM9004968 IFN6-LineC-Dif1-Sample2
- GSM9004969 IFN7-LineC-Dif2-Sample1
- GSM9004970 IFN8-LineD-Dif2-Sample1
- GSM9004971 CTRL1-LineD-Dif1-Sample1
- GSM9004972 CTRL2-LineD-Dif3-Sample1
- GSM9004973 CTRL3-LineD-Dif1-Sample2
- GSM9004974 CTRL4-LineC-Dif1-Sample1
- GSM9004975 CTRL5-LineC-Dif1-Sample2
- GSM9004976 CTRL6-LineC-Dif2-Sample1
- GSM9004977 CTRL7-LineD-Dif2-Sample1
- GSE300441 ERRα-KDM5C Restrains STING Enhancer Activity to Modulate Type I Interferon Signaling in Breast Cancer Progression 10 samples shares interferon, activity
- GSE255092 Interaction between HIV-1 Tat and EBV Zta favours immune escape of B cells by downregulating HLA-ABC expression 56 samples shares hla
- GSE239639 Trabectedin and olaparib combination primes cellular immunotherapy with HLA-independent killer lymphocytes against sarcoma preclinical models through the cGAS-STING pathway 24 samples shares hla
- GSE285257 Hypoxia impairs decitabine-induced expression of HLA-DR in acute myeloid leukaemia cell lines [RNA-seq] 18 samples shares hla
- GSE295194 Self and parasite-derived peptides selected upon DERAA-bearing HLA-DRB1 alleles activate CD4+ T cells from Chagas cardiomyopathy patients and are associated with ventricular dysfunction 16 samples shares hla
- GSE290615 miRNA/mRNA analysis of Chlamydia trachomatis-infected endometrial biopsies indicate increased TGF-β pathways drive epithelial-mesenchymal transition and regulatory T cell differentiation 15 samples shares hla
- GSE314941 Cohesin mutations suppress HLA class II gene expression to promote immune evasion during the progression to acute leukemia in children with Down syndrome 180 samples shares hla
- GSE314930 Cohesin mutations suppress HLA class II gene expression to promote immune evasion during the progression to acute leukemia in children with Down syndrome [CUT&Run] 72 samples shares hla
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.