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| Status |
Public on Jun 23, 2017 |
| Title |
CH_4 |
| Sample type |
RNA |
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| Source name |
CSF
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| Organism |
Homo sapiens |
| Characteristics |
diagnosis: Control headache
gender: f
age: 40
tissue: cerebral spinal fluid
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| Extracted molecule |
total RNA |
| Extraction protocol |
Total RNA was extracted from 200 μl of CSF or plasma using the miRCURY RNA isolation kit-biofluid (Exiqon) according to the manufacturer’s protocol
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| Label |
n/a
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| Label protocol |
3 µl of total RNA was processed by reverse transcriptase and pre-amplification steps following the manufacturer’s protocol (Applied Biosystems). The pre-amplification reaction was mixed with TaqMan OpenArray Real-Time PCR Master mix (1:1). The mix was loaded onto the OpenArray human panel (755 human miRNAs) using the Accufill System and ran using a QuantStudio 12K Flex PCR (Life Technologies).
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| Hybridization protocol |
n/a
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| Scan protocol |
n/a
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| Description |
Control
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| Data processing |
OpenArray profiling data were analysed in two steps. First, to ensure good quality detection and to avoid false-positives the data were filtered according to “AmpScore” or “CqConf” values provided by the ExpressionSuite software (ThermoFisher Scientific). Cutoff thresholds were set to 35. This gave us a general idea about microRNA expression in CSF. Second, more in depth data analysis was performed in R/Bioconductor (R Core Team, 2016; Huber et al., 2015) and a more stringent “present”/“absent” filtering step was included whereby a microRNA was considered “present” in a set of samples if the Ct was < 28 in 60% of the samples. A microRNA was considered “absent” if the Ct was > 28 in 80% of the same samples. MicroRNA were removed unless they were either present in both control/TLE or control/SE samples, or if they were absent from one set of samples and present in the other. Missing data points were imputed (Bioconductor package “Non-detects” (McCall et al., 2014)), the data was normalised to the geometric mean as implemented in Bioconductor package “HTqPCR” (Dvinge and Bertone, 2009) and corrected for batch effects due to sample origin (Bioconductor package “ComBat” (Johnson et al., 2007)). Differential expression analysis was performed using the limma package (Ritchie et al., 2015). P-values were adjusted for multiple testing by controlling the false discovery rate (FDR) according to the method of Benjamini and Hochberg (Benjamini and Hochberg, 1995).
Matrix normalized worksheet reports geometric mean normalized signal.
Fold Change worksheet reports log2FC, p.value and adj.p.value. FC was calculated as 2^-ΔΔCt, where -ΔΔCt = -[ΔCt_test -Δct_control]. Differential expression analysis was performed using the limma package (Ritchie et al., 2015). P-values were adjusted for multiple testing by controlling the false discovery rate (FDR) according to the method of Benjamini and Hochberg (Benjamini and Hochberg, 1995).
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| Submission date |
Jan 26, 2017 |
| Last update date |
Jun 23, 2017 |
| Contact name |
David Henshall |
| Organization name |
Royal College of Surgeons in Ireland
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| Street address |
123 St Stephens Green
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| City |
Dublin |
| ZIP/Postal code |
2 |
| Country |
Ireland |
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| Platform ID |
GPL22992 |
| Series (1) |
| GSE94108 |
Cerebrospinal fluid microRNAs are potential biomarkers of temporal lobe epilepsy and status epilepticus |
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| Supplementary data files not provided |
| Processed data are available on Series record |
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