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| Status |
Public on Oct 31, 2016 |
| Title |
2013_024_012 [non pathological renal tissue] |
| Sample type |
SRA |
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| Source name |
non pathological renal tissue
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| Organism |
Homo sapiens |
| Characteristics |
gender: male
age (yrs): 43
tissue type: non pathological renal tissue
pt-stage: CTRL
lymph node metastasis: CTRL
distand metastasis: CTRL
grading: CTRL
ajcc stage: CTRL
tumor size (cm): CTRL
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| Extracted molecule |
total RNA |
| Extraction protocol |
Fresh-frozen tissue samples (approximately 50 mg) were cut on liquid nitrogen and homogenized with Yttrium stabilized Zirkonoxid-Beads (Silibeads, Sigmund-Lindner, Warmensteinach, Germany) using a Precellys24 tissue homogenizer. Total RNA was isolated using the mirVana miRNA Isolation Kit (Ambion, Foster City, CA, USA) according to the manufacturers recommendation. To remove residual DNA fragments, we treated the isolate twice with DNase (DNA-free Kit, Ambion).
Libraries for small RNA sequencing were prepared using the TruSeq small RNA library kit (Illumina) according to the manufacturer’s instructions. 500 ng of total RNA was used as input for RNA adapter ligation, followed by reverse transcription and PCR amplification with bar-coded primers. Small RNA libraries were sequenced on a NextSeq500 (Illumina).
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| Library strategy |
miRNA-Seq |
| Library source |
transcriptomic |
| Library selection |
size fractionation |
| Instrument model |
Illumina NextSeq 500 |
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| Description |
Gene expression in non pathological renal tissue
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| Data processing |
After adapter trimming, reads were collapsed and mapped to the genome using Bowtie (Langmead et al., 2009)
Mapped reads were subsequently annotated to different contaminants (tRNA, rRNA, sn(o)RNA, piRNA, ...) and mature miRNAs using genome annotation data from Ensembl, UCSC and miRBase v20.
Prior to normalization, data were filtered using a cutoff of 4 reads. miRNA expression data were normalized based on the total read count per sample. Read count for each miRNA was divided by the total read count in that sample and multiplied by the median total read count across all samples. After normalization, data were log2-transformed.
The expression level of each miRNA unit is measured by the number of sequenced fragments that map to the transcript and represent count data. This measure is different from gene probe-based methods, such as microarrays or RT-qPCR.
Genome_build: Ensembl, UCSC and miRBase v20
Supplementary_files_format_and_content: abundance measurements; annex_*_phase1_*.txt contains processed data for GSM1891367-74; annex_*_phase2_*.txt contains processed data for GSM1891375-402; A brief description of each file is included in the 'readme.txt'
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| Submission date |
Sep 22, 2015 |
| Last update date |
May 15, 2019 |
| Contact name |
Jörg Ellinger |
| E-mail(s) |
joerg.ellinger@ukb.uni-bonn.de
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| Organization name |
Universitätsklinikum Bonn
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| Department |
Urologie
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| Street address |
Sigmund-Freud-Straße 25
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| City |
Bonnn |
| State/province |
NRW |
| ZIP/Postal code |
53127 |
| Country |
Germany |
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| Platform ID |
GPL18573 |
| Series (1) |
| GSE73342 |
Next Generation Sequencing of small non-coding RNAs in the tissue of patients with renal cell carcinoma |
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| Relations |
| BioSample |
SAMN04102743 |
| SRA |
SRX1274976 |
| Supplementary data files not provided |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
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