Myeloid PINK1 represses mtDNA release and immune signaling that impacts neuronal pathology in patient-derived idiopathic PD models
RNA-seq (gene expression) · human · 8 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
- 8 samples: 8 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 GSE313883_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 PRJNA1381735 and SRA study SRP655387. 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 8 sample titles: 8 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.
- GSM9377081 Mono_WT_NS
- GSM9377082 Mono_PiKO_NS
- GSM9377083 Mono_WT_IL
- GSM9377084 Mono_PiKO_IL
- GSM9377085 Mac_WT_NS
- GSM9377086 Mac_PiKO_NS
- GSM9377087 Mac_WT_IL
- GSM9377088 Mac_PiKO_IL
- GSE311180 Integrated Transcriptomic and Functional Analysis Reveals Tissue-Specific Molecular Pathology in Adolescent Idiopathic Scoliosis 21 samples shares idiopathic, pathology
- GSE282524 Aberrant Neuronal Connectivity and Network Activity of Neurons Derived from Patients with Idiopathic Schizophrenia 14 samples shares idiopathic, neuronal
- GSE150910 RNA-Sequencing of Chronic hypersensitivity pneumonitis compared with Idiopathic Pulmonary Fibrosis and Control Lung 288 samples shares idiopathic
- GSE307568 Patient-derived organoid – immune cell co-culture platform for therapeutics discovery in high-grade endometrial cancer 189 samples shares patient-derived
- GSE215274 Identification of Whole Blood Gene Expression Signature to Predict the Therapeutic Effect of Nintedanib in Idiopathic Pulmonary Fibrosis 177 samples shares idiopathic
- GSE317901 Unraveling cetuximab response in head and neck cancer with APHRODYTHE, a multi-omics patient-derived xenograft platform 114 samples shares patient-derived
- GSE334033 A Patient-Derived Xenograft Model Identifies AK1 as a Key Regulator of Metastatic Potential in Primary Triple-Negative Breast Cancer 105 samples shares patient-derived
- GSE291966 An annotated biobank of triple negative breast cancer patient-derived xenografts featuring treatment-naïve and longitudinal samples throughout neoadjuvant chemotherapy 92 samples shares patient-derived
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.