Transcriptome sequencing reveals expression characteristics of osteosarcoma before and after neoadjuvant chemotherapy
RNA-seq (gene expression) · human · 10 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)
- Topic
- OsteosarcomaThis series is part of our curated briefing on it.
- Samples
- 10 samples: 5 conditions, mostly in duplicateGroups 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 GSE218037_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 PRJNA901971 and SRA study SRP408094. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 10 samples.
How we read this: 5 replicated groups read from 10 sample titles; they account for 10 of them. 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.
- GSM6733268 A0 A
- GSM6733269 A1 A
- GSM6733270 B0 B
- GSM6733271 B1 B
- GSM6733272 D0 D
- GSM6733273 D1 D
- GSM6733274 E0 E
- GSM6733275 E1 E
- GSM6733276 F0 F
- GSM6733277 F1 F
- GSE218035 Long-read transcriptome sequencing reveals expression characteristics of osteosarcoma 36 samples same disease briefing · shares characteristics, osteosarcoma
- GSE21257 Genome-wide gene expression profiling on pre-chemotherapy biopsies of osteosarcoma patients who developed metastases within 5yrs (n=34) and patients who did not develop metastases within 5yrs (n=19) 53 samples same disease briefing · shares osteosarcoma, chemotherapy
- GSE154540 CDK4 overexpression is a predictive biomarker for resistance to conventional chemotherapy in osteosarcoma patients 50 samples same disease briefing · shares osteosarcoma, chemotherapy
- GSE253548 The whole transcriptome analysis using FFPE and fresh tissue samples identifies the molecular fingerprint of osteosarcoma 90 samples same disease briefing · shares osteosarcoma
- GSE317512 Age-stratified transcriptomic profiling reveals biologically distinct molecular phenotypes across pediatric, adolescent, and adult osteosarcoma 70 samples same disease briefing · shares osteosarcoma
- GSE245562 RNA sequencing to determine gene expression changes in SQLE knockdown osteosarcoma cells 6 samples same disease briefing · shares osteosarcoma
- GSE126209 Gene expression profiling in Osteosarcomas 23 samples same disease briefing · shares osteosarcoma
- GSE218036 Transcriptome analysis of osteosarcoma cell lines treated with FDA-approved drugs 18 samples same disease briefing · shares osteosarcoma
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.