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Delineating Tumor-infiltrating Antigen Presenting Cell populations

GSE61462 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2014/11/10 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 12 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
Mus musculus (mouse)
Samples
12 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)
The goal of this study is to compare tumor-infiltrating antigen presenting cell populations by global transcriptome profiling (RNA-seq) to help further delineate sub-populations of infiltrating myeloid cells in tumor. Methods: Four tumor antigen presenting cell populations were sorted from digested B78chOVA (melanoma variant) tumors in biological triplicate Results: RNA was extracted from the 4 groups (n=3 per group) and prepared for RNAseq.
Read the full summary ↓
Sequencing yielded ~405 million reads with an average read depth of 33.7 million reads/sample. Reads were then aligned to the mouse genome (UCSC mm10) and those that mapped uniquely to known mRNAs were used to assess differential expression.
This dataset
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.

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 GSE61462_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA261162 and SRA study SRP047171. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 12 more — browse all 12 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.