Select a Workflow
Variant callingIdentify nucleotide polymorphisms and short indels from Illumina and Element data.
Variant callingIdentify nucleotide polymorphisms and short indels from Illumina and Element data.
TranscriptomicsAnalyze bulk or single-cell RNA seq data using a variety of approaches.
TranscriptomicsAnalyze bulk or single-cell RNA seq data using a variety of approaches.
Single-Cell RNA-seq Preprocessing: 10X Genomics CellPlex Multiplexed SamplesComprehensive preprocessing for 10X Genomics CellPlex multiplexed single-cell RNA-seq data. Processes Cell Multiplexing Oligo (CMO) FASTQ files with CITE-seq-Count including required CellPlex-specific translation steps. Simultaneously processes gene expression FASTQ files with STARsolo and DropletUtils for alignment and cell filtering, and formats outputs for seamless import into Seurat/Scanpy (Read10X function).
Single-Cell RNA-seq Preprocessing: 10X Genomics v3 to Seurat and Scanpy Compatible FormatComplete preprocessing pipeline for 10X Genomics v3 single-cell RNA-seq data. Aligns raw FASTQ files using STARsolo, performs cell calling and quality filtering with DropletUtils, and formats outputs for seamless import into Seurat/Scanpy (Read10X function).
RNA-Seq Analysis: Paired-End Read Processing and QuantificationComplete RNA-Seq analysis for paired-end data: Processes raw FASTQ data through adapter and bad quality removal (fastp), alignment with STAR using ENCODE parameters, gene quantification via multiple methods (STAR and featureCounts), and expression calculation (FPKM with Cufflinks/StringTie, normalized coverage with bedtools). Produces count tables, normalized expression values, and genomic coverage tracks. Supports stranded and unstranded libraries, generating both HTSeq-compatible counts and normalized measures for downstream analysis.
RNA-Seq Analysis: Single-End Read Processing and QuantificationComplete RNA-Seq analysis for single-end data: Processes raw FASTQ data through adapter and bad quality removal (fastp), alignment with STAR using ENCODE parameters, gene quantification via multiple methods (STAR and featureCounts), and expression calculation (FPKM with Cufflinks/StringTie, normalized coverage with bedtools). Produces count tables, normalized expression values, and genomic coverage tracks. Supports stranded and unstranded libraries, generating both HTSeq-compatible counts and normalized measures for downstream analysis.
RegulationWorkflows for the analysis of ChIP-seq, ATAC-Seq, and beyond.
RegulationWorkflows for the analysis of ChIP-seq, ATAC-Seq, and beyond.
ATAC-seq Analysis: Chromatin Accessibility ProfilingComplete ATAC-seq analysis pipeline for paired-end reads. Processes raw FASTQ data through adapter and bad quality removal (cutadapt), alignment (Bowtie2 end-to-end), and filtering (removes MT reads, discordant pairs, low mapping quality <30, PCR duplicates). Generates 5' cut site pileups (±100bp), performs peak calling, and quantifies reads in 1kb summit-centered regions. Produces two normalized coverage tracks (per million mapped reads and per million reads in peaks) and fragment length distribution plots for quality assessment.
ChIP-seq Analysis: Paired-End Read ProcessingComplete ChIP-seq analysis for paired-end sequencing data. Processes raw FASTQ files through adapter removal (cutadapt), alignment to reference genome (Bowtie2), and stringent quality filtering (MAPQ >= 30, concordant pairs only). Peak calling with MACS2 optimized for paired-end reads identifies protein-DNA binding sites. Generates alignment files, peak calls, and quality metrics for downstream analysis.
ChIP-seq Analysis: Single-End Read ProcessingComplete ChIP-seq analysis for single-end sequencing data. Processes raw FASTQ files through adapter removal (cutadapt), alignment to reference genome (Bowtie2), and quality filtering (MAPQ >= 30). Peak calling with MACS2 uses either a fixed extension parameter or built-in model to identify protein-DNA binding sites. Generates alignment files, peak calls, and quality metrics for downstream analysis.
Consensus Peak Calling for ATAC-seq and CUT&RUN ReplicatesIdentifies high-confidence consensus peaks from ATAC-seq or CUT&RUN replicate experiments. The workflow calls peaks on individual replicates and identifies their intersection. To control for sequencing depth differences, it subsamples all replicates to the smallest library size, performs peak calling on the combined normalized data, and retains only peaks whose summits overlap with intersections from a user-defined minimum number of replicates.
CUT&RUN/CUT&TAG Analysis: Protein-DNA Interaction MappingComplete CUT&RUN/CUT&TAG analysis workflow for paired-end sequencing data. Processes raw FASTQ files through adapter removal (cutadapt) and alignment (Bowtie2 with dovetail option enabled). Applies quality filtering (MAPQ ≥ 30, concordant pairs only), converts BAM to BED format, and performs peak calling using MACS2 with parameters optimized for the punctate signal profile characteristic of CUT&RUN/CUT&TAG experiments.
Genome comparisonsWorkflows for creation of pairwise and multiple genome alignments.
Genome comparisonsWorkflows for creation of pairwise and multiple genome alignments.
Protein foldingAnalysis of protein folding using the ColabFold framework.
Protein foldingAnalysis of protein folding using the ColabFold framework.