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Status |
Public on Nov 21, 2023 |
Title |
FB226 |
Sample type |
SRA |
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Source name |
Primary breast cancer
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Organism |
Homo sapiens |
Characteristics |
gender: female dfs.time_months: 24.95081967 status: non-relapse
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Extracted molecule |
total RNA |
Extraction protocol |
RNA libraries were prepared for sequencing using standard DNBSEQ-T7RS(MGI) protocols
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Library strategy |
RNA-Seq |
Library source |
transcriptomic |
Library selection |
cDNA |
Instrument model |
DNBSEQ-T7 |
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Description |
S219000806FR
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Data processing |
Total RNA was extracted from FFPE samples using the QIAGEN FFPE RNeasy kit (QIAGEN GmbH, Hilden, Germany) RNA was analyzed using an Agilent RNA 6000 Nano Kit (Aglient Technologies, Santa Clara, CA, USA), and RNA integrity numbers were determined to evaluate RNA integration using an Agilent Bioanalyzer 2100 (Aglient Technologies, Santa Clara, CA, USA) An input of 500 ng of total RNA was amplified using an Ovation FFPE WTA System (NuGEN, San Carlos, CA, USA) NEBNext® Ultra™ II DNA Library Prep Kit (Illumina) was used for fragmentation and labelling The quality and quantity of amplified libraries were evaluated using Qubit (Invitrogen, Carlsbad, CA, USA) and Agilent Bioanalyzer 2100 (Aglient Technologies, Santa Clara, CA, USA). All libraries were sequenced using an DNBSEQ-T7RS (MGI) with 100 bp paired end reads Base call files were converted to fastq format using cal2Fastq. Raw data were normalized using the fastp (version 0.20.1) for data processing Supplementary_files_format_and_content: tab-delimited text files include read counts values for each Sample
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Submission date |
Nov 22, 2021 |
Last update date |
Nov 21, 2023 |
Contact name |
Wenhao Ouyang |
E-mail(s) |
[email protected]
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Phone |
18578330789
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Organization name |
Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University
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Street address |
Department of Medical Oncology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University
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City |
Guangzhou |
State/province |
GuangDong |
ZIP/Postal code |
510120 |
Country |
China |
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Platform ID |
GPL29480 |
Series (1) |
GSE189371 |
Radiomics Predicts High or Low Recurrence Risk and is Associated with LncRNAs in Breast Cancer |
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Relations |
BioSample |
SAMN23246019 |
SRA |
SRX13161441 |
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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