Quality assessment software tools | Genome-wide association study data analysis
GWAS result files are prone to errors due to the vast amount of data they contain and the different manner in which these data are generated by individual cohorts. Before combining data from individual studies in a meta-analysis, it is important to ensure that all data included are valid, of high quality and compatible between cohorts to reduce both the false-positive and the false-negative findings.
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 program for transforming sets of genotype data for use with the programs SNPTEST and IMPUTE. GTOOL can be used to 1) generate subsets of genotype data, 2) to convert genotype data between the PED file format and the file format used by SNPTEST and IMPUTE, 3) merge genotype datasets together and orient genotype data according to a strand file.
A typical use of QCTOOL is to compute per-sample and per-SNP summary statistics for a cohort, and use these to filter out samples and SNPs (either by removing them from the files or by writing exclusion lists). QCTOOL can also be used to perform various subsetting and merging operations, and to manipulate sample information in preparation for association testing.
Supports quality control and analysis of genome-wide association studies (GWAS). GWASTools provides functions for interactive investigation and includes intensity data. It can be used to verify pedigrees for accuracy, as well as to deduce pairwise relationships from. This tool can plot kinship coefficients and includes several options, including genotype cluster plots, B allele frequency (BAF)/ log R ratio (LRR) plots with chromosome ideograms, quantile-quantile plots and Manhattan plots.
Aims at improving the accuracy of the annotation of fungal genes. ABFGP is a method able to re-annotate gene models on a gene-by-gene basis by using informants. This application: (i) is species-independent, (ii) works without partial or whole-genome DNA alignments or supervision and (iii) can use a variable number of informant genes. It can complement ensemble predictors and can be incorporated into existing gene annotation pipelines.
Serves for an end-to-end multiparty computation (MPC) protocol for secure genome-wide association study (GWAS). Secure-GWAS suits for matrix multiplication, exponentiation and iterative algorithms with extensive data reuse patterns. This program utilizes cryptographic pseudorandom generators (PRGs) to diminish the overall communication cost. The main protocol can be used to detect a small number of significantly associated single-nucleotide polymorphisms (SNPs).
An R-package for fast quality control and data handling of multiple data files obtained from genome-wide association studies (GWAS). Thought to be employed as a preprocessing tool in the meta-analysis of GWA data, GWAtoolbox can process multiple GWA data files in a few minutes. Output consists in an extensive list of quality statistics and graphical output, to give a comprehensive overview of the data that are going to be meta-analyzed.