IGVF background | Knowledge graph of variant function | The rigvf package | Data license | Catalog API | GRanges-based queries | ArangoDB API | Use with Bioconductor | Compute overlap with plyranges | Plot variants with plotgardener | Session info

Experiment and sample description | Salmon quantification | Sample information | Acknowledgments | Session info

Standard workflow | Quick start | How to get help for DESeq2 | Acknowledgments | Funding | Input data | Why un-normalized counts? | The DESeqDataSet | Transcript abundance files and tximport / tximeta | Tximeta for import with automatic metadata | Count matrix input | htseq-count input | SummarizedExperiment input | Pre-filtering | Note on factor levels | Collapsing technical replicates | About the pasilla dataset | Differential expression analysis | Log fold change shrinkage for visualization and ranking | Speed-up and parallelization thoughts | p-values and adjusted p-values | Independent hypothesis weighting | Exploring and exporting results | MA-plot | Alternative shrinkage estimators | Plot counts | More information on results columns | Rich visualization and reporting of results | Exporting results to CSV files | Multi-factor designs | Data transformations and visualization | Count data transformations | Blind dispersion estimation | Extracting transformed values | Variance stabilizing transformation | Regularized log transformation | Effects of transformations on the variance | Data quality assessment by sample clustering and visualization | Heatmap of the count matrix | Heatmap of the sample-to-sample distances | Principal component plot of the samples | Variations to the standard workflow | Wald test individual steps | Control features for estimating size factors | Contrasts | Interactions | Time-series experiments | Likelihood ratio test | Extended section on shrinkage estimators | Recommendations for single-cell analysis | Approach to count outliers | Dispersion plot and fitting alternatives | Local or mean dispersion fit | Supply a custom dispersion fit | Independent filtering of results | Tests of log2 fold change above or below a threshold | Access to all calculated values | Sample-/gene-dependent normalization factors | "Model matrix not full rank" | Linear combinations | Group-specific condition effects, individuals nested within groups | Levels without samples | Theory behind DESeq2 | The DESeq2 model | Changes compared to DESeq | Methods changes since the 2014 DESeq2 paper | Count outlier detection | Expanded model matrices | Independent filtering and multiple testing | Filtering criteria | Why does it work? | Frequently asked questions | How can I get support for DESeq2? | Why are some p values set to NA? | How can I get unfiltered DESeq2 results? | How do I use VST or rlog data for differential testing? | Why after VST are there still batches in the PCA plot? | Do normalized counts correct for variables in the design? | Can I use DESeq2 to analyze paired samples? | If I have multiple groups, should I run all together or split into pairs of groups? | Can I run DESeq2 to contrast the levels of many groups? | Can I use DESeq2 to analyze a dataset without replicates? | How can I include a continuous covariate in the design formula? | I ran a likelihood ratio test, but results() only gives me one comparison. | What are the exact steps performed by DESeq()? | Is there an official Galaxy tool for DESeq2? | I want to benchmark DESeq2 comparing to other DE tools. | I have trouble installing DESeq2 on Ubuntu/Linux... | Session info | References

Introduction | Preparing tximeta input | Running tximeta | How does it work? | Packages used for caching metadata | Pre-computed digests | SummarizedExperiment output | Retrieve the transcript database | Add exons per transcript | Easy summarization to gene-level | Assign ranges by abundance | Add different identifiers | Differential gene expression analysis | Differential transcript expression and usage analysis | Additional metadata slots | Mixed reference transcripts | salmon mixed reference | Importing oarfish data | Errors connecting to a database | What if digest isn't known? | Linked transcriptomes | Clear linkedTxomes | Loading linkedTxome JSON files | Clear linkedTxomes again | alevin details | Other quantifiers | Acknowledgments | Session info | References

The Swish method | Quick start | Macrophage stimulation experiment | Data import | Read in the column data from CSV | Add a column pointing to your files | Read in quants with tximeta | Differential transcript expression | Running Swish at the transcript level | Plotting results | Differential gene expression | Running Swish at the gene level | Plotting gene results | Differential transcript usage | Interaction designs | Condition and secondary covariates | Create and check paired samples | Swish for interaction effects | Plotting interaction results | Allelic expression analysis | Correlation test | alevin scRNA-seq | Further details | Analysis types supported by Swish | Accounting for continuous variables | Structure of tximeta output | Plotting q-values over statistics | Plotting InfRV | Salmon in alignment mode, how to use tximeta | Permutation schemes for interactions | Session information | References

Experiment and sample description | Salmon quantification | Sample information | SummarizedExperiment | Acknowledgments | Session info

Inferential replicate data moved to Zenodo | Sample information and quantification files | Genome and gene annotation file | Cufflinks | RSEM | kallisto | Salmon | alevin | oarfish | Sailfish | Session info

Introduction | Acknowledgments | Version Info | R serialization | saveRDS and readRDS | Reading RDS files in Python | Cross-release stability | HDF5-backed storage | Saving with HDF5Array | SummarizedExperiment and AnnData | The alabaster ecosystem | saveObject and readObject | Validation with takane | BED format for ranges | Writing BED files | Saving metadata columns | Saving Seqinfo separately | Propagating object metadata | Summary and recommendations | Session info

Introduction | Quick start | Method overview | Steps before bootstrapping | Import excluded regions | Genome segmentation | Bootstrapping ranges | Assessing properties of bootstrap samples | Bootstrapping and plyranges | Counting the total number of overlaps | Computing the sum of signal value for nearby peaks | Block bootstrapping one region | Visualizing bootstrap types | Session information | References

Ranges revisited | Constructing Ranges | Arithmetic on Ranges | Grouping Ranges | Restricting Ranges | Summarising Ranges | Joins, or another way at looking at overlaps between Ranges | Finding your neighbours | Example: dealing with multi-mapping | Grouping by overlaps | Data Import/Output | Learning more | Namespace considerations | Session information

Obtaining sample information from GEO | Downloading FASTQ files from SRA | Aligning reads | Counting reads | Information on the RangedSummarizedExperiment | Information on the genes | Session information

Introduction | Experimental data | Preparing quantification input to DESeq2 | Transcript quantification and tximport / tximeta | Quantifying with Salmon | Reading in data with tximeta | DESeq2 import functions | SummarizedExperiment | Branching point | The DESeqDataSet object, sample information and the design formula | Starting from SummarizedExperiment | Starting from count matrices | Exploratory analysis and visualization | Pre-filtering the dataset | The variance stabilizing transformation and the rlog | Sample distances | PCA plot | PCA plot using Generalized PCA | MDS plot | Differential expression analysis | Running the differential expression pipeline | Building the results table | Other comparisons | Multiple testing | Plotting results | Counts plot | MA-plot | Gene clustering | Independent filtering | Independent Hypothesis Weighting | Annotating and exporting results | Exporting results | Plotting fold changes in genomic space | Removing hidden batch effects | Using SVA with DESeq2 | Using RUV with DESeq2 | Time course experiments | Appendix | Updated details on quantification | Downloading FASTQ files | Building the salmon index | Quantifying abundance with salmon | Producing a RangedSummarizedExperiment with tximeta | Session information | References

Quick overview | About Ranges | Example: finding GWAS hits that overlap known exons | Session information

Introduction | Quick start | Method overview | Linking transcripts to TSS | Importing allelic counts | Filtering features | Global allelic imbalance | Plotting results | Differential allelic imbalance | Dynamic allelic imbalance | More complex designs | Further questions | Session info | References

Background | Matching with matchRanges() | Assessing quality of matching | Visualizing matching results | Compare CTCF sites | Session information

Background | Matching with matchRanges() | Assessing quality of matching | Visualizing matching results | Compare CTCF site orientation | Session information

Introduction | Terminology | Methodology | Using matchRanges() | Assessing quality of matching | Accessing matched data | Using cobalt to assess balancing | Choosing the method parameter | Nearest-neighbor matching | Rejection sampling | Stratified sampling | Class structure | Implementation details | Session information | References

Session information

Introduction | Obtaining example data | Creating the focal and pool sets | Obtaining the matched set with matchRanges() | Assessing covariate balance

Choice of methods | Related work | Further description of matching and bootstrapping | In other words | Options and features | Consideration of excluded regions | References

eds package for reading in Alevin EDS format | About EDS | Simple example of reading EDS into R: | Session info

Allelic counts of D melanogaster x D simulans cross | Additional details

Getting help | Introduction | Methods | Simulation | Operation | Quantification and data import | DTU testing | Workflow | Salmon quantification | Importing counts into R/Bioconductor | Transcript-to-gene mapping | Statistical analysis of differential transcript usage | DRIMSeq | stageR following DRIMSeq | Post-hoc filtering on the standard deviation in proportions | DEXSeq | stageR following DEXSeq | Citing methods in published research | DTU analysis complements DGE analysis | DGE analysis with DESeq2 | DGE analysis with edgeR | End of workflow section | Discussion | Session information | Software versions | Data availability | Acknowledgments | References

Object construction