Provides analysis, management and visualization tools for next-generation sequencing (NGS) data. Strand NGS supports extensive workflows for alignment, RNA-seq, small RNA-seq, DNA-seq, Methyl-seq, MeDIP-seq and ChIP-seq experiments. This tool includes standard differential expression analysis for different experimental conditions, as well as differential splicing analysis. It can notice variants in the transcriptome and gene fusion events.
Automates the process of genotyping microsatellite repeats in Huntington disease (HD) data. ScaleHD is a pipeline designed to be used for large-scale automated genotyping of HTT GAC/CCG repeat parallel sequencing data. It performs quality control, sequence alignment and genotyping on all file pairs presented by the user as input. The pipeline consists of three main stages: sequence quality control (SeqQC), sequence alignment (SeqALN) and automated genotyping (GType).
A python toolkit providing best-practice pipelines for fully automated high throughput sequencing analysis. You write a high level configuration file specifying your inputs and analysis parameters. This input drives a parallel pipeline that handles distributed execution, idempotent processing restarts and safe transactional steps. The goal is to provide a shared community resource that handles the data processing component of sequencing analysis, providing researchers with more time to focus on the downstream biology.
A pipeline for efficiently detecting and genotyping high-quality variants from large-scale sequencing data. GotCloud automates sequence alignment, sample-level quality control, variant calling, filtering of likely artifacts using machine-learning techniques, and genotype refinement using haplotype information. The pipeline can process thousands of samples in parallel and requires less computational resources than current alternatives. Experiments with whole-genome and exome-targeted sequence data generated by the 1000 Genomes Project show that the pipeline provides effective filtering against false positive variants and high power to detect true variants.
An integrated analysis pipeline for whole-exome sequencing (WES) data analysis. Fastq2vcf offers improved flexibility, efficiency, and reproducibility. It can generate shell scripts that automate the steps for processing WES data from raw sequence reads to annotated variants. It is also highly configurable and provides users with complete control of the processing procedure, making it easy to submit and track jobs in both single workstation and parallelized computing environments.
A variant detection pipeline designed to process high throughput sequencing data, with the purpose of identifying potentially pathogenic mutations. Cpipe offers an industry standard variant calling pipeline with a suite of additional features needed by diagnostic laboratories added on top.
Support a series of analyses commonly required for targeted resequencing and whole exome sequencing data, including: single-nucleotide and insertion/deletion variant calling, copy number analysis, and cohort-based analyses.