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.

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 general/datasets/Cms_hipp1115/processing.rtf | 3 +++
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 create mode 100644 general/datasets/Cms_hipp1115/processing.rtf

(limited to 'general/datasets/Cms_hipp1115/processing.rtf')

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+<p><strong>Outlier Detection.&nbsp;</strong>Samples 7 (J-CR-21), 24 (N-R-29), and 40 (D-R-6) were detected as outliers and have abnormal expression profiles (i.e. they do not cluster with other samples and have abnormal median and quartile ranges after normalization. These samples have been removed from the analysis.</p>
+
+<p><strong>RMA Algorithm.&nbsp;</strong>The Robust Multichip Analysis (RMA) algorithm fits a robust linear model at the probe level to minimize the effect of probe-specific affinity differences. This approach: n Increases sensitivity to small changes between experiment and control samples. n Minimizes variance across the dynamic range, but does compress calculated fold change values. RMA consists of three steps: 1. Background adjustment 2. Quantile normalization 3. Summarization This is a multi-chip analysis approach. Therefore, all arrays intended for comparison should be included together in the summarization step. For a more detailed description of the RMA algorithm, see the publication, Exploration, Normalization, and Summaries of High Density Oligonucleotide Array Probe Level Data, Biostatistics, April 2003; Vol. 4; Number 2: 249&ndash;264.</p>
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