GEO series

a-CGH of Esophageal Cancer (70 cases)

GSE54993 Homo sapiens (human) Genome variation profiling by genome tiling array 70 samples Submitted 2014/03/11 Platform GPL8736

At a glance

human · 70 samples

Organism: Homo sapiens (human)
Samples: 70 samples
Data you can get: A processed table (series matrix) and supplementary files from NCBI.

Summary (written by the submitters)

Esophageal cancer is one of the most aggressive cancers and the sixth leading cause of cancer death worldwide. Approximately 70% of the global esophageal cancers occur in China and over 90% histopathological forms of this disease are esophageal squamous cell carcinoma (ESCC). Currently, there are limited clinical approaches for early diagnosis and treatment for ESCC, resulting in a 10% 5-year survival rate for the patients.

Read the full summary ↓

Meanwhile, the full repertoire of genomic events leading to the pathogenesis of ESCC remains unclear. Here we show a comprehensive genomic analysis in 158 ESCC cases, as part of the International Cancer Genome Consortium (ICGC) Research Projects (http://icgc.org/icgc/cgp/72/371/1001734). We conducted whole-genome sequencing in 17 ESCC cases and whole-exome sequencing in 71 cases, of which 53 cases and additional 70 ESCC cases were subjected to array comparative genomic hybridization (a-CGH) analysis.

This dataset

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Download · which file do I need?

Direct links to NCBI, 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.

All supplementary files ↗

3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE54993_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

Also filed as BioProject PRJNA238221. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 24670651) ↗

Samples in this study

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+ 70 more — browse all 70 samples with per-sample file links →

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