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Differential analysis of HOXA1 in adult cells at isoform resolution by RNA-Seq [Illumina]

GSE37703 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2012/12/11 Platform GPL15520Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 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
Homo sapiens (human)
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)
High-throughput RNA sequencing (RNA-Seq) has enabled accurate gene discovery and expression estimation, but robust differential analysis of gene and transcript abundances has proven difficult. We present a new algorithm, implemented in the freely available tool Cuffdiff, which integrates transcript-level expression estimation with a method to control for variability across replicate samples.
Read the full summary ↓
Cuffdiff robustly identifies differentially regulated isoforms and genes and reveals differential splicing or promoter-preference changes. We demonstrate the accuracy of our approach through differential analysis of lung fibroblasts in response to loss of the developmental transcription factor HOXA1 and uncover a critical role for this gene in the maintenance of adult cells. We show that HOXA1 is required for lung fibroblast and HeLa cell cycle progression, and loss of HOXA1 results in significant expression level changes in thousands of individual transcripts, along with isoform switching events in key regulators of the cell cycle.
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 GSE37703_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 PRJNA162905 and SRA study SRP012607. 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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