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资源简介：
RNA-seq of ovarian cancer ascites cells
应用场景：
创建时间：
2018-02-01
相关数据集
Paired bulk and single-cell RNA-seq on high-grade serous ovarian cancer (HGSOC) samples. Paired bulk and single-cell RNA-seq on high-grade serous ovarian cancer (HGSOC) samples
We have sequenced ovarian tumors in several different ways: 1) poly-A captured scRNA-seq, 2) poly-A captured pooled scRNA-seq in pools of 4 samples each 3) Bulk RNA-seq on ribo-depleted tumor chunks 4
NIAID Data Ecosystem100
Paired bulk and single-cell RNA-seq on high-grade serous ovarian cancer (HGSOC) samples
We have sequenced ovarian tumors in several different ways: 1) poly-A captured scRNA-seq, 2) poly-A captured pooled scRNA-seq in pools of 4 samples each 3) Bulk RNA-seq on ribo-depleted tumor chunks 4
NIAID Data Ecosystem30
Comparison of the differentially expressed genes in normal vs ovarian cancer cells. Comparison of the differentially expressed genes in normal vs ovarian cancer cells
Identification of the differentially expressed genes in the cancer cells (mainly focusing on the growth factor receptors) Overall design: High coverage deep sequencing of the transcriptome was perform
NIAID Data Ecosystem10
Long noncoding RNA and mRNA expression profile in ovarian cancer. Long noncoding RNA and mRNA expression profile in ovarian cancer
Comparison of epithelial ovarian tissue and epithelial ovarian cancer. Overall design: Human ovarian tissue samples including 3 normal tissue samples and 6 malignant ovarian tissue samples. lncRNA and
NIAID Data Ecosystem40
Comparison of the differentially expressed genes in normal vs ovarian cancer cells
Identification of the differentially expressed genes in the cancer cells (mainly focusing on the growth factor receptors) High coverage deep sequencing of the transcriptome was performed using the Ill
NIAID Data Ecosystem30
