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diff --git a/general/datasets/Jax_liver_agil_mdp_0113/experiment-type.rtf b/general/datasets/Jax_liver_agil_mdp_0113/experiment-type.rtf new file mode 100644 index 0000000..073f544 --- /dev/null +++ b/general/datasets/Jax_liver_agil_mdp_0113/experiment-type.rtf @@ -0,0 +1,13 @@ +
+
+Liver histopathology.
+Paraffin-embedded liver tissue was cut to 5-μm sections in duplicate and stained with hematoxylin and eosin. Liver injury in the left liver lobe was blindly scored by A.H.H. and confirmed by a certified veterinary pathologist. Necrosis was quantified by unbiased stereology using a point-counting technique (Mouton, 2002). Briefly, a grid with 100 evenly spaced points was overlaid on printed images of liver sections taken at ×100 magnification. The total number of points lying in an area of necrosis was divided by the total number of points lying completely within the entire tissue section to determine a percent necrosis score (0–100%). The necrosis score for each animal in the study is publicly available from the Mouse Phenome Database (http://phenome.jax.org/pub-cgi/phenome/mpdcgi?rtn = projects/details&sym = Threadgill1).
+
+RNA isolation.
+To eliminate variability in transcript expression that might arise between liver lobes, the left liver lobe was selected for the remainder of the data analysis and gene expression profiling. RNA was extracted from the 30 mg of tissue derived from the left lobe of sample livers using the Qiagen RNeasy kit (Qiagen, Valencia, CA). RNA concentrations were measured using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE), and quality was verified using the Agilent Bio-Analyzer (Agilent Technologies, Santa Clara, CA). RNA was determined to be of good quality for use in microarray hybridizations if the 28S:16S rRNA ratio was greater than 1.8 and the 260/280 nm absorbance ratio was in the range of 1.9–2.1.
+
+Microarray hybridizations.
+In this study, all RNA samples were hybridized to arrays individually; none were pooled. RNA amplifications and labeling were performed using Low RNA Input Linear Amplification kits (Agilent Technologies). For hybridization, 750 ng of total RNA from each mouse liver was amplified and labeled with fluorescent dye (Cy5). In parallel, 750 ng of a common reference RNA (Icoria, Inc., RTP, NC) was labeled with the fluorescent dye, Cy3, in order to standardize analysis of global gene expression between mouse strains (Bammler et al., 2005). Labeled cRNA was then processed and hybridized to Agilent Mouse Toxicology Arrays (catalog# 4121A, 22,575 features) according to the manufacturer's protocol. Details regarding the microarray probe set on the 4121A array are available via the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc = GPL891). Following hybridization, arrays were washed using a custom protocol developed by Icoria, Inc. Briefly, array gaskets were removed under immersion in wash solution 1 (6× sodium chloride/sodium phosphate/EDTA [SSPE], 0.005% N-lauroylsarcosine). Arrays were washed with wash solution 1 and incubated for 1 min with gentle agitation on a magnetic stir plate. A second incubation was performed in wash solution 2 (0.06× SSPE, 0.005% N-lauroylsarcosine).
+
+Data analysis of significantly changed transcripts.
+Raw microarray intensity values were obtained from Agilent Feature Extraction software (v8.5) and archived in the UNC Microarray Database (http://genome.unc.edu). Raw data are available to the public through this database. The log2 ratio of Cy5/Cy3 intensity was normalized using locally weighted scatterplot smoothing to eliminate intensity bias of features. Transcripts with fewer than 70% available data across samples were excluded from the analysis, reducing the probe list to 15,509 transcript probes. Available data are defined as those probes that are neither saturated nor below the limit of quantification. Intensity ratios were transformed to eliminate hybridization batch effects using the batch normalization feature in Partek Genomics Suite (Partek, Inc., St Louis, MO). Analysis of significant transcripts was performed using an analysis of covariance (ANCOVA) model in Partek in which the main effects were mouse strain, treatment, the interaction of mouse strain and treatment, and the sample necrosis score. Transcripts were called significantly different if the p value was less than a threshold determined by a step-down false discovery rate (FDR, Benjamini and Liu, 1999) (α = 0.01) to correct for multiple comparisons across array features. Heat maps were generated using hierarchical agglomerative clustering.
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