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Sas jmp10 genomics version 6

Manufactured by SAS Institute
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SAS JMP10 Genomics, version 6 is a software platform designed for the analysis and visualization of genomic data. It provides a comprehensive set of tools and algorithms for tasks such as gene expression analysis, genome-wide association studies, and sequence data analysis. The software is intended to assist researchers and scientists working in the field of genomics and bioinformatics.

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3 protocols using sas jmp10 genomics version 6

1

Arabidopsis Gene Expression Profiling

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For gene expression profiling, total RNA was extracted as described above and converted to biotinylated antisense cDNA according to the Affymetrix standard labeling protocol. The resulting cDNA was hybridized to the Arabidopsis AraGene-1_0-st-type (Affymetrix) as described in (10 (link)).
A Custom CDF Version 20 with TAIR-based gene definitions was applied for array annotation (51 (link)). Raw intensity values were RMA background corrected and quantile normalized. One-way analysis of variance (ANOVA) was performed to identify differentially expressed genes using SAS JMP10 Genomics, version 6, from SAS (SAS Institute, Cary, NC, USA). A false-positive rate of a = 0.05 with FDR correction was taken as the level of significance. Venn diagrams were created with the public available analysis tool of the Bioinformatic & Evolutionary Genomic server (http://bioinformatics.psb.ugent.be/webtools/Venn).
GSEA was performed by using the fgsea package (52 ) for R v3.4.0 (53 ). Pathways belonging to various cell functions were obtained from Kyoto Encyclopedia of Genes and Genomes (www.genome.jp/kegg).
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2

Transcriptomic Analysis of NAA20 in Arabidopsis

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The peqGOLD Total RNA Kit (Peqlab) was used to extract RNA from 17-day-old wildtype and naa20 seedlings grown on 1×MS medium with or without 2 mM DTT under short-day conditions. A global transcriptome analysis was performed using the GeneChip Arabidopsis Gene 1.0 ST Arrays from Affymetrix (High Wycombe, United Kingdom) as described in Linster et al. (2015) (link). The arrays were annotated with a Custom CDF Version 16 with TAIR-based gene definitions. Quantile normalization and RMA background correction were applied to normalize the raw fluorescence intensity values. Differentially expressed genes were identified with the commercial software package SAS JMP10 Genomics, version 6, from SAS (SAS Institute, Cary, NC, United States). The applied false discovery rate correction allowed for a false-positive rate of alpha = 0.05 as the level of significance. Transcripts differentially regulated (>2-fold up- or downregulated, p < 0.05) in naa20 and wildtype in response to DTT were functionally annotated. Overrepresented biological processes were identified based on the DAVID Bioinformatics Resources 6.8 gene ontology analysis (Huang et al., 2009 (link)). For this purpose, only processes with a gene count of ≥5 and a value of p < 0.05 were taken into account.
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3

Differential Expression Analysis of RMS

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Expression of LEF1 and CTNNB1 was also evaluated in a publicly available RMS microarray data set [20 (link)] (available at ftp://caftpd.nci.nih.gov/pub/caARRAY/experiments/caArray_trich-00099/,). A Custom CDF Version 20 with ENTREZ based gene definitions was used to annotate the arrays. The Raw fluorescence intensity values were normalized applying quantile normalization and RMS background correction. An ANOVA was performed to identify differential expressed genes using a commercial software package SAS JMP10 Genomics, version 6, from SAS (SAS Institute, Cary, NC, USA). A false positive rate of a = 0.05 with FDR correction was taken as the level of significance.
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