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Systematic profiling of synovial sarcoma transcriptome

GSE144190 Homo sapiens (human) RNA-seq (gene expression) 20 samples Submitted 2022/02/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 20 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
Soft tissue sarcomaThis series is part of our curated briefing on it.
Samples
20 samples
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.
Summary (written by the submitters)
We systematically explored the transcriptome of 10 synovial sarcoma (SS) patients. We detected a large number of upregulated and downregulated genes in SS compared to normal tissues, which were mainly involved in cell cycle, metabolic and P53 signaling pathways. Moreover, we identified a multitude of differentially alternative spliced genes, indicating that the deregulation of alternative splicing could be one of main factors contribute to the tumorigenesis of SS.
Read the full summary ↓
A set of tumor-specific gene fusion pairs were identified in SS. We also detected dozens of differentially expressed circRNAs and their parental genes were enriched in muscle related biological process. The interaction network constructed based on circRNAs, miRNAs and corresponding target genes showed that the differentially expressed circRNAs in SS have the potential to regulate the expression of a number of SS related genes. Collectively, we systematically investigated the abnormal expression profile of SS and gain insights into the molecular mechanism from different views of transcriptome expression changes.
This dataset
Open GSE144190 in finder → Find more human RNA-seq datasets → Soft tissue sarcoma landscape →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE144190_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA602962 and SRA study SRP244471. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 36118864) ↗
Samples in this study

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+ 20 more — browse all 20 samples with per-sample file links →

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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.