Expression Bioinformatics

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Expression Bioinformatics von Mind Map: Expression Bioinformatics

1. 2. Descriptive Statistics

1.1. Histograms

1.2. QQ-plots

1.3. pdf / cdf

1.4. MA-plot

1.5. Boxplots

1.6. estimator of location

1.6.1. Quantiles

1.6.2. Mean

1.6.3. Median

1.6.4. Tukey's Biweight

1.7. Estimator Deviation

1.7.1. Variance

1.7.2. MAD

1.8. Scatter Plots

2. 4. Raw Expression Data

2.1. Raw Data

2.1.1. Image

2.1.2. Reads

2.2. Spot finding

2.2.1. spotted circle

2.2.2. in situ squares

2.3. Segmentation

2.3.1. foreground

2.3.2. background

2.4. Quantification

2.4.1. foreground intensity

2.4.2. background intensity

2.5. Quality assessment

2.5.1. Uniformity

2.5.2. Spots

2.5.3. Array wide

2.5.4. Histograms

2.6. RNA Seq

2.6.1. Reads

3. 5. Normalization

3.1. Intra-array (MAS5)

3.1.1. Trimmed Mean

3.1.2. Tukeys Biweight

3.2. Inter-array

3.2.1. 2 arrays

3.2.1.1. Linear Regression

3.2.1.1.1. y = ax + b

3.2.1.1.2. Least Squares Error

3.2.1.2. Non-linear (Lowess) regression

3.2.1.2.1. Piecewise linear regression functions

3.2.1.3. Invariant probe regression

3.2.1.3.1. Invariant Sets

3.2.1.3.2. Invariant difference selection algorithm

3.2.1.3.3. Rank vectors

3.2.1.3.4. Order preserving

3.2.2. >= 2 arrays

3.2.2.1. multiple linear regression

3.2.2.2. Distribution (Quantile) normalization

3.2.2.2.1. QQ plots

3.2.2.2.2. Permutations

3.2.2.3. global scaling, centering

3.2.2.3.1. means

3.3. RNA-seq normalization

3.3.1. gene bias

3.3.1.1. relative length

3.3.1.1.1. rpk(G)

3.3.2. sample bias

3.3.3. technical bias

4. 1. Transcriptome Technologies

4.1. Microarray

4.1.1. Dual Dye experiment

4.1.2. Single dye experiment

4.1.3. Raw Data: monochrome image

4.2. RNA-Seq (NGS)

4.2.1. Raw Data: Reads