MSKCC Study 1- Mapping the Temporal Impact of Perturbations on Lineage Plasticity and Gene Regulation
Single-cell RNA-seq · human · 22 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Homo sapiens (human)
- Samples
- 22 samples: 22 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.
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 GSE288587_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJEB85005 and SRA study ERP168459. 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 22 sample titles: 22 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.
- GSM8770302 Sample_A_transcriptome, WT
- GSM8770303 Sample_B_transcriptome, WT
- GSM8770304 Sample_C_transcriptome, WT
- GSM8770305 Sample_D_transcriptome, WT
- GSM8770306 Sample_E_transcriptome, WT
- GSM8770307 Sample_F_transcriptome, WT
- GSM8770308 Sample_G_transcriptome, KO
- GSM8770309 Sample_H_transcriptome, KO
- GSM8770310 Sample_I_transcriptome, KO
- GSM8770311 Sample_J_transcriptome, KO
- GSM8770312 Sample_L_transcriptome, KO
- GSM8770313 Sample_A_larry, WT
- GSM8770314 Sample_B_larry, WT
- GSM8770315 Sample_C_larry, WT
- GSM8770316 Sample_D_larry, WT
- GSM8770317 Sample_E_larry, WT
- GSM8770318 Sample_F_larry, WT
- GSM8770319 Sample_G_larry, KO
- GSM8770320 Sample_H_larry, KO
- GSM8770321 Sample_I_larry, KO
- GSM8770322 Sample_J_larry, KO
- GSM8770323 Sample_L_larry, KO
- GSE288991 Emerin Dysregulation Drives the Very-Small-Nuclear Phenotype and Lineage Plasticity that Associates with a Clinically Aggressive Subtype of Prostate Cancer 18 samples shares plasticity, lineage
- GSE309034 Combined BET Bromodomain and DNMT Inhibition Targets Lineage Plasticity in Prostate Cancer [BETi_DNMTi_human_RNAseq] 44 samples shares plasticity, lineage
- GSE324131 A single-cell and spatial atlas of prostate cancer reveals the combinatorial nature of gene modules underlying lineage plasticity and metastasis 38 samples shares plasticity, lineage
- GSE269904 A temporal factorial dissection of kidney organoid differentiation identifies the impact of WNT, FGF, BMP and GDF signaling on ‘off-target’ patterning 30 samples shares temporal, impact
- GSE275859 Acute myeloid leukemia with mixed phenotype is characterized by stemness features with limited lineage plasticity 20 samples shares plasticity, lineage
- GSE295834 Circadian regulator REV-ERBα is a master regulator of tumor lineage plasticity and an effective therapeutic target [RNA-Seq] 18 samples shares plasticity, lineage
- GSE296115 The Histone Methyltransferase KMT2D is a Critical Mediator of Lineage Plasticity and Therapeutic Response in Castration Resistant Prostate Cancer [LNCaP Bulk RNA-Seq] 16 samples shares plasticity, lineage
- GSE302864 DNMT3B drives neuroendocrine lineage plasticity and aggressive progression in prostate cancer 12 samples shares plasticity, lineage
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.