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SC3-consensus clustering of single cell RNA-Seq data

GSE79102 Homo sapiens Expression profiling by high throughput sequencing 192 samples Submitted 2017/02/16 Platform GPL11154
Summary
We report a new unsupervised clustering tool for single cell RNA-seq data called SC3. We show that biologically relevant information can be obtained from preneoplastic cells of patients with myeloprolifertive disease.
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Direct links to NCBI, no account and no request form: the whole study as GSE79102_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 192 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA314949 and SRA study SRP071643. Searching any of these in the dataset finder brings you back here.

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