From b2feda451ccfbeaed02dce9088d6dd228cf15861 Mon Sep 17 00:00:00 2001 From: Bonface Date: Tue, 13 Feb 2024 23:52:26 -0600 Subject: Update dataset RTF Files. --- general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/processing.rtf | 5 +++++ 1 file changed, 5 insertions(+) create mode 100644 general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/processing.rtf (limited to 'general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/processing.rtf') diff --git a/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/processing.rtf b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/processing.rtf new file mode 100644 index 0000000..acc1087 --- /dev/null +++ b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/processing.rtf @@ -0,0 +1,5 @@ +

RNA-sequencing and analysis

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Monocytes from single optic nerve heads or from peripheral blood (restrained cheek bleed) were FAC sorted into 100 μl buffer RLT + 1% βME and frozen at − 80 °C until further processing. Samples were defrosted on ice and homogenized by syringe in RLT Buffer (total volume 300 μl). Total RNA was isolated using RNeasy micro kits as according to manufacturer’s protocols (Qiagen) including the optional DNase treatment step, and quality was assessed using an Agilent 2100 Bioanalyzer. The concentration was determined using a Ribogreen Assay from Invitrogen. Amplified dscDNA libraries were created using a Nugen Ovation RNA-seq System V2 and a primer titration was performed to remove primer dimers from the sample to allow sample inputs as low as 50 pg RNA. The SPIA dscDNA was sheared to 300 bp in length using a Diogenode Disruptor. Quality control was performed using an Agilent 2100 Bioanalyzer and a DNA 1000 chip assay. Library size produced was analysed using qPCR using the Library Quantitation kit/Illumina GA /ABI Prism (Kapa Biosystems). Libraries were barcoded, pooled, and sequenced 6 samples per lane on a HiSeq 2000 sequencer (Illumina) giving a depth of 30–35 million reads per sample.

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Following RNA-sequencing samples were subjected to quality control analysis by a custom quality control python script. Reads with 70% of their bases having a base quality score ≥ 30 were retained for further analysis. Read alignment was performed using TopHat v 2.0.7 [34] and expression estimation was performed using HTSeq [35] with supplied annotations and default parameters against the DBA/2 J mouse genome (build-mm10). Bamtools v 1.0.2 [36] were used to calculate the mapping statistics. Differential gene expression analysis between groups was performed using edgeR v 3.10.5 [37] following, batch correction using RUVSeq, the removal of outlier samples and lowly expressed genes by removing genes with less than five reads in more than two samples. Normalization was performed using the trimmed mean of M values (TMM). Unsupervised HC was performed in R (1-cor, Spearman’s rho). Following preliminary analysis, 1 sample was removed as an outlier. Adjustment for multiple testing was performed using false discovery rate (FDR). Genes were considered to be significantly differentially expression at a false discovery rate (FDR; q) of q < 0.05. Pathway analysis was performed in R, IPA (Ingenuity Pathway Analysis, Qiagen), and using publically available tools (see Results).

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