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Diverse and Targetable Kinase Alterations Drive Histiocytic Neoplasms

GSE74442 Homo sapiens (human) RNA-seq (gene expression) 13 samples Submitted 2015/11/11 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 13 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
13 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)
Histiocytic neoplasms are clonal, hematopoietic disorders characterized by an accumulation of abnormal, monocyte-derived dendritic cells or macrophages in Langerhans Cell (LCH) and non-Langerhans (non-LCH) histiocytoses, respectively. The discovery of BRAFV600E mutations in ~50% of these patients provided the first molecular therapeutic target in histiocytosis.
Read the full summary ↓
However, recurrent driving mutations in the majority of BRAFV600E-wildtype, non-LCH patients are unknown, and recurrent cooperating mutations in non-MAP kinase pathways are undefined for the histiocytic neoplasms. Through combined whole exome and transcriptome sequencing, we identified recurrent kinase fusions involving BRAF, ALK, and NTRK1, as well as recurrent, activating MAP2K1 and ARAF mutations in BRAFV600E-wildtype, non-LCH patients. In addition to MAP kinase pathway lesions, recurrently altered genes involving diverse cellular pathways were identified. Treatment of MAP2K1- and ARAF-mutated, non-LCH patients using MEK and RAF inhibitors, respectively, resulted in clinical efficacy demonstrating the importance of detecting and targeting diverse kinase alterations in these disorders.
This dataset
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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 GSE74442_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 PRJNA300424 and SRA study SRP065445. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 26566875) ↗
Samples in this study

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+ 13 more — browse all 13 samples with per-sample file links →

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