RiverXData is an open-source initiative focused on driving innovation in bioinformatics, and multiomics research. We build scalable tools, workflows, and libraries designed to support complex experimental designs across bioinformatics applications. Our mission is to empower researchers with accessible, high-performance, and modern solutions for data analysis and integrative multiomics. Contact for work: [email protected]

• river-slurm: The standard setup for SLURM cluster (High performance computing) to power the data analysis.
• river-utils: The CLI tool for setting up the remote environments and river-platform management.
• river: A secure bioinformatics data platform for centralized storage, analysis, and management — all with unified authorization and access control which also supports the nf-core ecosystem.

• visual-studio-code-server: Visual studio code server for working with HPC remotely
• rstudio-server: Rstudio server for working with HPC remotely
• jupyterlab: Jupyterlab server for working with HPC remotely

GWAS

• bioinfor-wf-nipt-human-genetics: A workflow for performing GWAS analysis using NIPT sequencing data
• UKB-RAP-Notebooks-Genomics: The notebooks for working with UKB-RAP- a largest human WES/WGS biobank data platform.

• sarek: Variant calling pipeline for germline and somatic variants from whole genome, exome, or targeted sequencing data. Supports tumor/normal analyses.
• rnaseq: RNA-seq processing pipeline that includes quality control, alignment or pseudo-alignment, quantification, and generation of gene expression matrices.
• ampliseq: Amplicon sequencing pipeline for microbial community profiling, such as 16S rRNA gene sequencing.
• quantms: Quantitative proteomics pipeline for label-free and isobaric labeling analyses using both DDA and DIA data.
• taxprofiler: Taxonomic profiling pipeline for shotgun metagenomics, supporting multiple tools and producing standardized outputs.
• methylseq: DNA methylation analysis pipeline using bisulfite-treated sequencing data. Supports multiple aligners and provides comprehensive QC.
• circrna: Pipeline for detecting and quantifying circular RNAs (circRNAs) from RNA-seq data, including miRNA target prediction.
• mag: Metagenomic pipeline for assembling, binning, and annotating metagenome-assembled genomes (MAGs) from short or long reads.
• atacseq: ATAC-seq pipeline to identify open chromatin regions, perform peak calling, and assess data quality with various QC metrics.
• rnafusion: Fusion detection pipeline using RNA-seq data, combining results from multiple fusion detection tools into reports and visualizations.

• smartsensor: The sensor utilizes a smartphone camera with machine learning to analyze and characterize chemical compounds.
• enhancer-predictor: The pipeline to predict the enhancer

We welcome contributions from the community! Whether it's bug fixes, feature suggestions, or documentation improvements, every contribution helps drive bioinformatics research forward.

• Website: riverxdata.com
• GitHub: RiverXData GitHub

Join us on this journey to revolutionize data analysis in proteomics and beyond!