A comprehensive R package to construct interactive and reproducible biological data analysis applications based on the R platform
-
Updated
Jan 8, 2023 - R
A comprehensive R package to construct interactive and reproducible biological data analysis applications based on the R platform
Computational Suite for Bioinformaticians and Biologists (CSBB) is a RShiny application developed with an intention to empower researchers from wet and dry lab to perform downstream Bioinformatics analysis
This tutorial is created for educational purpose
R package: Simulate Expression data from igraph network using mvtnorm (CRAN; JOSS)
Ensemble Learning for Harmonization and Annotation of Single Cells (ELeFHAnt) provides an easy to use R package for users to annotate clusters of single cells, harmonize labels across single cell datasets to generate a unified atlas and infer relationship among celltypes between two datasets. It uses an ensemble of three machine learning classif…
R package MiscMetabar: Miscellaneous functions for metabarcoding analysis
Multple methods for BSA Pipeline
A flexible, automation and pragmatic workflow tool to process the NGS data.
Algorithm to implement Fraction and Allelic Copy number Estimate from Tumor/normal Sequencing using unmatched normal sample(s) for log ratio calculations
Algorithm to implement Fraction and Allelic Copy number Estimate from Tumor/normal Sequencing using unmatched normal sample(s) for log ratio calculations
A QC pipeline for SVs calls based on coverage and SNP calls
R/Bioconductor package for e/iCLIP data analysis
An R package for RNAseq differential expression analysis and visualization, in an easy and reproducible way.
process and analyze paired-end ATAC-Seq data
🧽 Estimate sequencing saturation for GEX, VDJ, and ADT data from the 10x Genomics platform.
Tumor in normal detection
a shiny frontend for the nextflow-bcl pipeline
Bioinformatic pipeline for SARS-CoV-2 sequence analysis
Source code to support the paper: "Extensive mitochondrial population structure and haplotype-specific variation in metabolic phenotypes in the Drosophila Genetic Reference Panel"
Add a description, image, and links to the ngs-analysis topic page so that developers can more easily learn about it.
To associate your repository with the ngs-analysis topic, visit your repo's landing page and select "manage topics."