Software Platforms

KGG
KGGA systematic biological Knowledge-based mining system for Genome-wide Genetic studies
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KGG (Knowledge-based mining system for Genome-wide Genetic studies) is a software tool to perform knowledge-based secondary analyses of p-values from genome-wide association studies (GWAS). The knowledge-based secondary analyses include gene-based, gene-pair-based and gene-set based association analysis.It is implemented by Java with a user-friendly graphic interface to facilitate data analysis and result visualization. Build on advanced algorithms, it is able to process up to 10 million variants in several hours with 15GB RAM on a workstation.
KGGSeq
KGGSeqA biological Knowledge-based mining platform for Genomic and Genetic studies using Sequence data
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KGGSeq is a software platform constituted of Bioinformatics and statistical genetics functions making use of valuable biologic resources and knowledge for sequencing-based genetic mapping of variants/genes responsible for human diseases/traits. Simply, KGGSeq is like a fishing rod facilitating geneticists to fish the genetic determinants of human diseases/traits in the big sea of DNA sequences. Compared with other genetic tools like plink/seq, KGGSeq paid more attention downstream analysis of genetic mapping. Currently, a comprehensive and efficient framework was newly implemented on KGGSeq to filter and prioritize genetic variants from whole exome sequencing data.
KGGSEE
KGGSEEA biological Knowledge-based mining platform for Genomic and Genetic association Summary statistics using gEne Expression
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KGGSEE is a standalone Java tool for knowledge-based secondary analyses of genomic and genetic association summary statistics of complex phenotypes by integrating gene expression and related data. It has four major integrative analyses, 1) unconditional gene-based association guided by expression quantitative trait loci (eQTLs), 2) conditional gene-based association guided by selective expression in tissues or cell types, 3) estimation of phenotype-associated tissues or cell-type based on gene expression in single-cell or bulk cells of different tissues, and 4) causal gene inference for complex diseases and/or traits based-on multiple eQTL. More integrative analysis functions will be added into this analysis platform in the future.
FAPI
FAPIFast and Accurate P-value Imputation for genetic association
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FAPI is a powerful multi-thread Java-based application developed to infer p-values of untyped Single-nucleotide polymorphisms (SNPs) through p-values of SNPs in LD with the untyped one. With similar imputation accuracy to other genotype imputation tools (including IMPUTE and MACH), FAPI is superfast, without requiring phases of reference genotypes and any sample raw genotypes.
SnpTracker
SnpTrackerTool to track SNPs
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SnpTracker is a Java-based tool developed to extract the latest version rsID and genomic coordinates of SNPs given any version of rs ID(s) according to the SNP track history RsMergeArch, coordinates data SNPChrPosOnRef and deleted history SNPHistory in dbSNP.
IGG
IGGA tool to Integrate Genotypes for genome-wide Genetic Studies
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IGG is an open-source Java package with graphic interface to efficiently and consistently integrate genotypes across high throughput genotyping platforms (e.g., Affymetrix and Illumina), the HapMap genotype repository (http://www.hapmap.org/), and even genotypes from the collaborators’ projects. It is equipped with a series of functions to control qualities of genotype integration and to flexibly export genotypes for genetic studies as well.
GEC
GECGenetic Type I Error Calculator
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The Genetic Type I error calculator (GEC) is a Java-based application developed to address multiple-testing issue with dependent Single-nucleotide polymorphisms (SNPs).
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Web Apps

REZ
REZRobust-regression z-score
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REZ (robust-regression z-score) is a powerful approach to calculate tissue selective expression of genes. The website provides query and tissue enrichment analysis of genes' selective expression produced by REZ.
SPA
SPASingle-cell type and phenotype cross annotataion framework
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The website provides two functions, i.e., browsing the the association signals bwtween all pre-computed phenotype-cell cluster pairs, and customizing your annotation by inputing expression profile of single cell clusters or GWAS summary statistics. The website have included more than 20,000 single cell clusters and about1,000 GWAS datasets.
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