# Welcome to CytoProfile

**CytoProfile** is an R package designed for advanced cytokine data
analysis. It provides a comprehensive suite of functions for
exploratory, univariate, and multivariate analysis as well as machine
learning methods tailored to your cytokine datasets.

## Key Features

- **Exploratory Analysis:**  
  Quickly generate enriched bar plots, boxplots, and summary statistics
  to assess your data.

- **Statistical Testing:**  
  Perform t-tests, ANOVA, and other univariate methods with ease.

- **Multivariate Analysis:**  
  Utilize PCA, PLS-DA, and other techniques for deeper insights.

- **Machine Learning:**  
  Integrate Random Forest and XGBoost models for predictive analysis.

- **Data Handling:**  
  Seamlessly load and preprocess cytokine data for efficient analysis.

You can install the development version of CytoProfile from
[GitHub](https://github.com/saraswatsh/CytoProfile/tree/devel) with:

``` r
# install.packages("devtools")
devtools::install_github("saraswatsh/CytoProfile", ref = "devel")
```

Install CytoProfile from CRAN with:

``` r
install.packages("CytoProfile")
```

## Learn More

- [Getting
  Started](https://cytoprofile.cytokineprofile.org/articles/getting_started.md):
  A detailed tutorial to help you start using CytoProfile.
- [Function
  Reference](https://cytoprofile.cytokineprofile.org/reference/index.md):
  Complete documentation for all functions.
- [GitHub Repository](https://github.com/saraswatsh/CytoProfile): Access
  the source code and contribute.

# Package index

## Exploratory Analysis

Functions for exploring raw data, summarizing statistics, and
visualizing key patterns.

- [`cyt_anova()`](https://cytoprofile.cytokineprofile.org/reference/cyt_anova.md)
  :

  ANOVA Analysis on Continuous Variables. **\[deprecated\]**

- [`cyt_ttest()`](https://cytoprofile.cytokineprofile.org/reference/cyt_ttest.md)
  :

  Two Sample T-test Comparisons. **\[deprecated\]**

- [`cyt_bp()`](https://cytoprofile.cytokineprofile.org/reference/cyt_bp.md)
  : Boxplots for Continuous Variables with Optional Grouping

- [`cyt_bp2()`](https://cytoprofile.cytokineprofile.org/reference/cyt_bp2.md)
  :

  Boxplot Function Enhanced for Specific Group Comparisons.
  **\[deprecated\]**

- [`cyt_errbp()`](https://cytoprofile.cytokineprofile.org/reference/cyt_errbp.md)
  : Error-bar Plot

- [`cyt_skku()`](https://cytoprofile.cytokineprofile.org/reference/cyt_skku.md)
  : Distribution of the Data Set Shown by Skewness and Kurtosis.

- [`cyt_volc()`](https://cytoprofile.cytokineprofile.org/reference/cyt_volc.md)
  : Volcano plot

- [`cyt_heatmap()`](https://cytoprofile.cytokineprofile.org/reference/cyt_heatmap.md)
  : Heat Map

- [`cyt_dualflashplot()`](https://cytoprofile.cytokineprofile.org/reference/cyt_dualflashplot.md)
  : Dual-flashlight Plot

- [`cyt_univariate()`](https://cytoprofile.cytokineprofile.org/reference/cyt_univariate.md)
  : Pairwise Univariate Tests Between Two Groups

- [`cyt_univariate_multi()`](https://cytoprofile.cytokineprofile.org/reference/cyt_univariate_multi.md)
  : Univariate Tests for Multi‑Level Categorical Predictors

- [`cyt_violin()`](https://cytoprofile.cytokineprofile.org/reference/cyt_violin.md)
  : Violin Plots for Continuous Variables with Optional Grouping

- [`apply_scale()`](https://cytoprofile.cytokineprofile.org/reference/apply_scale.md)
  : Apply a scale transformation to numeric columns

- [`adjust_p()`](https://cytoprofile.cytokineprofile.org/reference/adjust_p.md)
  : Adjust p-values using a specified method

## Multivariate Analysis

Functions for deeper multivariate insights.

- [`cyt_splsda()`](https://cytoprofile.cytokineprofile.org/reference/cyt_splsda.md)
  : Analyze data with Sparse Partial Least Squares Discriminant Analysis
  (sPLS-DA).
- [`cyt_pca()`](https://cytoprofile.cytokineprofile.org/reference/cyt_pca.md)
  : Analyze Data with Principal Component Analysis (PCA) for Cytokines.
- [`cyt_mint_splsda()`](https://cytoprofile.cytokineprofile.org/reference/cyt_mint_splsda.md)
  : Analyze data with Multivariate INTegration (MINT) Sparse Partial
  Least Squares Discriminant Analysis (sPLS-DA).

## Machine Learning Methods

- [`cyt_rf()`](https://cytoprofile.cytokineprofile.org/reference/cyt_rf.md)
  : Run Random Forest Classification on Cytokine Data,
- [`cyt_xgb()`](https://cytoprofile.cytokineprofile.org/reference/cyt_xgb.md)
  : Run XGBoost Classification on Cytokine Data.

## Utility Functions

- [`cyt_export()`](https://cytoprofile.cytokineprofile.org/reference/cyt_export.md)
  : Generic export function for Cytokine plots

## Datasets

- [`ExampleData1`](https://cytoprofile.cytokineprofile.org/reference/ExampleData1.md)
  : Example Cytokine Profiling Data 1.
- [`ExampleData2`](https://cytoprofile.cytokineprofile.org/reference/ExampleData2.md)
  : Example Cytokine Profiling Data 2.
- [`ExampleData3`](https://cytoprofile.cytokineprofile.org/reference/ExampleData3.md)
  : Example Cytokine Profiling Data 3.
- [`ExampleData4`](https://cytoprofile.cytokineprofile.org/reference/ExampleData4.md)
  : Example Cytokine Profiling Data 4.
- [`ExampleData5`](https://cytoprofile.cytokineprofile.org/reference/ExampleData5.md)
  : Example Cytokine Profiling Data 5.

# Articles

### Getting Started

- [Getting Started with
  CytoProfile](https://cytoprofile.cytokineprofile.org/articles/getting_started.md):