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Status |
Public on Apr 10, 2022 |
Title |
Dog E - Bone |
Sample type |
SRA |
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Source name |
Bone
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Organism |
Canis lupus familiaris |
Characteristics |
tissue: Bone dog breed: Great Pyranees source location: Phalanx P2
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Extracted molecule |
total RNA |
Extraction protocol |
Bone: RNA extracted according to Nance et al (Nance R, Agarwal P, Sandey M, Starenki D, Koehler J, Sajib AM, et al. A method for isolating RNA from canine bone. Biotechniques. 2020 Jun;68(6):311–7). Osteosarcoma Tumor: RNA extracted using Tri-Reagent + mechanical homogenization RNA sequencing libraries were produced with 500 ng of total RNA using the TruSeq PolyA library kit (Illumina) to deplete samples of any RNA aside from polyadenylated mRNA. They were pooled and sequenced on two lanes of the Illumina HiSeq v4 (PE, 50 bp, 25 M reads)
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Library strategy |
RNA-Seq |
Library source |
transcriptomic |
Library selection |
cDNA |
Instrument model |
Illumina HiSeq 4000 |
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Data processing |
Quality - FASTQC (v 0.10.1) was used to assess the read quality Trimming - Trimmomatic (v 0.39) was used to remove the adapters, first leading base, and reads with a minimum length of 36 bp. After trimming, approximately 32-45 million reads remained for each sample. FASTQC was used again to confirm all bases had a Phred quality score above 28. Mapping - Reads were mapped to the indexed canine reference genome (CanFam3.1) obtained from ENSEMBL using HiSat2 (v 2.2.1) and a table of mapped read counts was generated with Stringtie (v 1.3.3) Differential Gene Expression Analysis - DEseq2 (v 3.14) was used to identify differentially expressed genes in tumor vs. bone. A multi-factor design was used for a paired analysis to include patient ID as a random effect in the design formula (design = ~dog + tissue source) to account for differences between individuals Filtering - Genes with less than 1 read were excluded. To extract significant DEGs while minimizing noise, the data was filtered using a false discovery rate (FDR) less than 0.05, base mean greater than 10, and log2 fold-change greater than 1 and less than −1 (corresponding to a fold-change of 2 and −2, respectively). Individual Level Analysis - Variance stabilizing transformation (vst) function in DEseq2 was used on the significant DEGs (padj<0.05, base mean<10, log2FC>1,<-1); log2 fold-change values for each gene were derived by subtracting the variance stabilized transformed counts (on the log2 scale) of bone from tumor for each dog Assembly: CanFam3.1 Supplementary files format and content: Gzipped, tab-delimiited text file inlcuding raw gene counts for every gene and every sample
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Submission date |
Mar 26, 2022 |
Last update date |
Apr 10, 2022 |
Contact name |
Xu Wang |
E-mail(s) |
xzw0070@auburn.edu
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Organization name |
Auburn University
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Department |
Pathobiology, College of Veterinary Medicine
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Street address |
273 CASIC Building, Auburn Research Park, 559 Devall Dr
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City |
Auburn University |
State/province |
AL |
ZIP/Postal code |
36849 |
Country |
USA |
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Platform ID |
GPL24229 |
Series (1) |
GSE199489 |
Transcriptomic Analysis of Canine Osteosarcoma from a Precision Medicine Perspective Reveals Limitations of Differential Gene Expression Studies |
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Relations |
BioSample |
SAMN26992213 |
SRA |
SRX14624689 |
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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