Homo sapiens
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: GSE25292
PROVIDER: PRJNA142565 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR079377.fastq.gz | Fastqsanger.gz | |||
| SRR079378.fastq.gz | Fastqsanger.gz | |||
| SRR079379.fastq.gz | Fastqsanger.gz | |||
| SRR079380.fastq.gz | Fastqsanger.gz | |||
| SRR079381.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 8 |
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Project description:We characterized the expression patterns of sense-antisense transcripts, based on available cDNA sequences, in colon (colorectal) cancer tissues and in normal tissues surrounding the cancer tissues. Although expression balances (ratios) of most of sense and antisense transcript pairs did not change between patients or between normal and cancer tissues, we found 68 sense-antisense transcripts whose expression balances were altered specifically in colon cancer tissues.
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Project description:We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease. Global transcriptome profilings of 7 samples in normal and 7 samples in cancer from clinical breast tissue using Sage-Seq
2010-10-05 | E-GEOD-24491 | biostudies-arrayexpress
Project description:We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around 5 million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less abundant genes including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease.
2010-10-05 | GSE24491 | GEO
Project description:We characterized the expression patterns of sense-antisense transcripts, based on available cDNA sequences, in colon (colorectal) cancer tissues and in normal tissues surrounding the cancer tissues. Although expression balances (ratios) of most of sense and antisense transcript pairs did not change between patients or between normal and cancer tissues, we found 68 sense-antisense transcripts whose expression balances were altered specifically in colon cancer tissues. We conducted DNA microarray analyses by using the same set of probes designed for 2621 sense-antisense pairs to detect transcripts expressed in colon cancer tissues. These probes comprise 2358 pairs for the detection of protein-coding transcripts only, 250 pairs for the detection of protein-coding transcripts paired with non-protein-coding transcripts, and 13 pairs for the detection of non-protein-coding transcripts only.
2011-03-01 | E-GEOD-14398 | biostudies-arrayexpress
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