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Status |
Public on Apr 22, 2013 |
Title |
mouse miRNA array diabetic_4 |
Sample type |
RNA |
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Source name |
skeletal muscle
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Organism |
Mus musculus |
Characteristics |
group: diabetic strain: C57BL/KsJ db+
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Extracted molecule |
total RNA |
Extraction protocol |
Total miRNA from tissue sample was isolated from control and diabetic skeletal muscle using Ambion miRNA isolation kit as per manufacture's instruction
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Label |
Cy3
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Label protocol |
Briefly, 100 ng of total RNA was dephosphorylated with calf intestine alkaline phosphatase for 30 min at 37°C. Denaturation was performed by adding DMSO and incubating at 100°C for 7 min and immediately transferred to a ice water bath. Ligation was performed with pCp-Cy3 at 16 °C for 2 h. The labeled samples were dried completely in a vacuum concentrator and resuspended in 18 ul of nuclease free water.
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Hybridization protocol |
The hybridization mixture (10X GE blocking agent (4.5µl) and 2X Hi-RPM hybridization buffer (22.5µl)) along with the labelled miRNA sample was heated for 5 min at 100 °C and immediately cooled on ice. Each 45 µL sample was hybridized onto a microarray at 55 °C for 20 h. Slides were then washed for 5 min in GE wash buffer 1 at RT and again for 5 min in GE wash buffer 2 at 37 °C, followed by an acetonitrile wash for 1 min at RT to dry the slides completely.
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Scan protocol |
Slides were scanned on a microarray scanner (G2565BA, Agilent) at 100 and 5% XDR settings. Agilent Feature Extraction software version 9.3.5 was used to extract the raw data.
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Description |
miRNA expression in diabetic skeletal muscle
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Data processing |
From raw data, gBG Sub Signal from four control and treated samples was taken for further analysis. Then median of all signals was taken and this was used as an input file for normalization by using R method. After normalization by R method, we obtained output file in which we applied Z-score statistical test. Given below is the algorithm used to generate normalized data provided in the VALUE column. Algorithm used in R for data normalization Step1: x<- read.table("input_file.txt",header=T,row.names=1,sep="\t") Step 2: log_x<-log(x,base=2) Step3: attach(log_x ) Step4: cnt<-(1/8)*(sort(Signal_1)+sort(Signal_2)+sort(Signal_3)+sort(Signal_4)+ sort(Signal_5)+sort(Signal_6)++sort(Signal_7)+sort(Signal_8)) Step5: value_1<-c(rank(Signal_1)) Step6: value_2<-c(rank(Signal_2)) Step7: value_3<-c(rank(Signal_3)) Step8: value_4<-c(rank(Signal_4)) Step9: value_5<-c(rank(Signal_5)) Step10: value_6<-c(rank(Signal_6)) Step11: value_7<-c(rank(Signal_7)) Step12: value_8<-c(rank(Signal_8)) Step13: final<-cbind(value_1,value_2,value_3,value_4,value_5,value_6,value_7,val ue_8) boxplot(final) Step14: write.table(final,"f//priyanka/R method/result.txt") Step15: write.table(final,"result.txt")
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Submission date |
Sep 26, 2011 |
Last update date |
Apr 22, 2013 |
Contact name |
Malabika Datta |
E-mail(s) |
mdatta@igib.res.in
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Phone |
91 11 27667602
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Organization name |
Institute of Genomics and Integrative Biology
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Street address |
Mall Road
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City |
Delhi |
ZIP/Postal code |
110 007 |
Country |
India |
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Platform ID |
GPL8824 |
Series (1) |
GSE32376 |
Control vs Diabetic mice skeletal muscle miRNA microarray |
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