Introduction | Installation | Example data | How missing values are represented | Filtering, log2 transformation and normalization | Imputation of missing values | The workflow in a single call | Where the processed data are stored | Differential abundance results | Relationship with the missing values | Detection and non-detection patterns between conditions | Visualizing the results | Interactive figures | Static figure | NADIA and related Bioconductor packages | What NADIA adds | Using NADIA together with other packages | Next steps | Session information

Introduction | Installation | The sample annotation | A simulated batch effect | Step 1: is the design suitable for batch correction? | Step 2: how much variance does the batch explain? | Why the default hides it, and what to do | Step 3: correct, and keep the biology | Protecting a variable inside ComBat | Step 4: verify | Did the batch effect go? | Did the biology survive? | What it changed in the results | Removing two factors, one after the other | Inspecting the correction with PCA | Applying the workflow to a real batch effect | The batch has to be declared, not discovered | The decomposition finds it | Correcting it, and checking against biology | Visual assessment with PCA | Statistical significance and fold-change magnitude | References | Session information

Introduction | Installation | The experiment | Declaring the truth | Scoring a pipeline | The metrics_table summary | How TP, FP, TN and FN are defined | The confusion plots: the whole picture at once | Species-level confusion plot | Overall confusion plot | The metrics heatmap | The OpDEA metrics | Interpreting ROC curves | The full ROC curve | Zooming into the low-FPR region | Comparing search engines across FPR ranges | Volcano plots as diagnostic tools | Comparing multiple pipelines | Comparing TP, FP, TN and FN | Ranking pipelines with the OpDEA criteria | Comparing saved results and external pipelines | What this benchmark can and cannot show | References | Session information

Introduction | Installation and packages | Normalization | What normalization does | Normalization methods available in NADIA | How normalization methods are evaluated | Comparing normalization methods with NADIA | Imputation | Why values are missing | How NADIA represents missing intensities | Imputation methods available in NADIA | How imputation methods are evaluated | Comparing imputation methods with NADIA | Applying the selected combination | Effect on differential abundance results | Practical decision guide | References and software | Session information

Introduction | DIA: Spectronaut | DIA: DIA-NN | Declaring the experimental design | TMT: Proteome Discoverer | Label-free: Proteome Discoverer | Bioconductor: SummarizedExperiment | Where the design comes from | Naming the conditions | Five sources, one common object | Sample information | Identification evidence | Quantities and downstream analysis | Session information

Introduction | Installation | Why values are missing | How NADIA represents missing intensities | Diagnosing missingness in the example data | Data processing shapes the missing-value pattern | Imputation strategies available in NADIA | Why one method may not represent every gap | The default hybrid: combo | softHybrid: a continuous combination | limpa: detection-aware estimates with uncertainty | Choosing among the strategies | References and software | Session information

Introduction | Setup and example data | Running Pattern Profiler | Selecting proteins for clustering | Choosing the number of clusters | Understanding the soft-clustering output | Visualizing the expression patterns | Protein profiles within each cluster | Comparing cluster centroids | Saving and reusing the results | Saving the long-format table as Parquet | Storing Pattern Profiler in a NADIA project | Practical recommendations | References | Session information

Introduction | Prepare an example analysis | Install and load NADIA | Run the processing workflow | Choose an output for the task | Export tabular results | Choose between TSV and Parquet | Create a set of TSV and/or Parquet files | Archive a complete analysis | Write and read a .nadia file | Restore and verify the result | Inspect stored tables and provenance | Query or extract the archive | Combine differential abundance with clustering | Explore results with interactive tables | Save interactive HTML | Save a complete widget page | Save an individual widget as one file | Preserve reproducibility | References | Session information

Introduction | Setup and example data | Installation | Processing the example dataset | Choosing the appropriate visualization | Interactive and static output | Highcharts license | Volcano plots | Summarizing the selected comparison | Creating and reading the plot | Labeling selected proteins and multiple comparisons | Boxplots of sample distributions | Comparing assays numerically | Creating and reading the boxplot | Principal component analysis | Comparing protein subsets | Creating and reading the PCA plot | Subset modes, ellipses, and sample filtering | Heatmaps | Selecting proteins for the heatmap | Creating and reading a focused heatmap | Annotations and repeated heatmaps | Protein pattern clusters | Building and summarizing the example clusters | Comparing cluster centroids | Inspecting representative protein profiles | Colors and consistent presentation | Exporting figures and data | Interactive charts | Static heatmaps | Practical recommendations | Session information