R Code Module 2

Vectorized operations

Apply functions to entire vectors efficiently

Conditional filtering

Select data based on complex conditions

Statistical analysis

Calculate means, variances, and other statistics

Quality control

Identify and handle problematic samples

&

AND operator used for multiple conditions

|

OR operator used for multiple conditions

subset()

Function used for cleaner syntax when filtering

which()

Function used to find row positions

%in%

Operator for matching against multiple values

gsub()

Function used with regex to remove or replace specific parts of a string

which.max()

Function used to find the index of the highest value

arrayInd()

Function used to convert a linear index to row and column positions

quantile()

Function used to find percentile thresholds

apply()

Function used to apply operations across rows using margin 1, and columns using margin 2

sapply()

Function used for simpler operations

lapply()

Function used when you need list output

strsplit()

Function used to parse strings into components

Mean difference

Metric that identifies genes with consistent expression changes between conditions

Variance

Metric that indicates how much expression varies within each condition

Combined analysis

Method prioritizing genes with large mean differences and low variance as reliable candidates for differential expression

aggregate()

Function used for grouped calculations

by()

Function used for applying functions by groups to calculate detailed statistics

tapply()

Function used for simple grouped operations

split()

Function used to divide data into group

Here is a comprehensive list of terms and definitions extracted from the "2B

pdf

P

values

Effect sizes

Magnitude of observed differences

Multiple testing

Adjusting for multiple comparisons in gene expression analysis

t.test()

A function used to determine if mean differences are statistically significant when comparing two groups

var.equal = FALSE

A parameter used for unequal variances, which is the default for gene expression

apply() with MARGIN = 1

A function used to test each gene or row individually at once

Log transformation (log2)

A technique used to stabilize variance and make highly skewed raw RNA

sapply()

A function used to extract p

p.adjust()

A function used to apply multiple testing corrections

Bonferroni correction

A very conservative multiple testing correction method

FDR (False Discovery Rate) correction

A multiple testing correction method that is more appropriate for genomics

ks.test() (Kolmogorov

Smirnov test)

KS statistic

A metric from normality testing where 0 indicates a perfect match to normal and 1 indicates it is completely different

Pearson correlation

A measurement of linear relationships between samples

Spearman correlation

A rank

cor()

A function used to calculate correlation coefficients

cor.test()

A function used for testing the significance of correlations

boxplot() with formula notation

Used for group comparisons to visualize gene expression differences

order()

Used to find the most significant gene by ordering results, such as by p

col parameter

Used to specify different colors by group in a plot

legend()

Used to add legends to plots to show the different groups or colors

Volcano plots

Visualizations that display statistical significance versus biological effect size for differential expression analysis

plot()

Used to create scatter plots, such as volcano plots showing fold change versus transformed p

log2()

Used for calculating fold changes in differential expression analysis

log10()

abline()

Used to add significance threshold lines, such as p=0.05 and 2

text()

Used to label significant genes on a volcano plot or to add correlation values as text overlay on a heatmap

Correlation heatmaps

Visualizations that show the relationships between samples

cor()

Used to calculate correlation matrices, such as using the Pearson method

image()

Used to create heatmap visualizations, which can be combined with text overlays

heat.colors()

Used to define color schemes for heatmap visualizations

axis()

Used to add axis labels to plots, such as adding sample names to a heatmap