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SHAPEIT specifications

Information


Unique identifier OMICS_12566
Name SHAPEIT
Alternative name Segmented HAPlotype Estimation and Imputation Tool
Software type Application/Script
Interface Command line interface
Restrictions to use Academic or non-commercial use
Operating system Unix/Linux, Mac OS
Programming languages C++
License MIT License
Computer skills Advanced
Version 4
Stability Stable
Maintained Yes

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Maintainer


  • person_outline Olivier Delaneau

Publications for Segmented HAPlotype Estimation and Imputation Tool

SHAPEIT citations

 (574)
library_books

Genome wide haplotype association analysis of primary biliary cholangitis risk in Japanese

2018
Sci Rep
PMCID: 5958065
PMID: 29773854
DOI: 10.1038/s41598-018-26112-1

[…] Haplotype phase was computationally estimated using SHAPEIT v2.79 for whole chromosomes with unphased SNP genotypes for all 2,886 unrelated samples in the combined study cohort. To improve phasing accuracy, we used 1000 Genomes Phase 3 genetic map reco […]

call_split

Polygenic pleiotropy and potential causal relationships between educational attainment, neurobiological profile, and positive psychotic symptoms

2018
PMCID: 5954124
PMID: 29765027
DOI: 10.1038/s41398-018-0144-4
call_split See protocol

[…] data on 664,907 autosomal SNPs.We then performed genotype imputation, using the phased haplotypes from the 1000 Genomes Project dataset as the reference panel. Prephasing and imputation was done with SHAPEIT and IMPUTE2,. The imputation was performed with the default parameters of the software. The final imputed dataset consisted of 9.7 million autosomal SNPs. […]

call_split

Sex specific glioma genome wide association study identifies new risk locus at 3p21.31 in females, and finds sex differences in risk at 8q24.21

2018
Sci Rep
PMCID: 5943590
PMID: 29743610
DOI: 10.1038/s41598-018-24580-z
call_split See protocol

[…] ation from Hardy-Weinberg equilibrium (HWE) (p < 1 × 10−5). Additional details of quality control procedures have been previously described in Melin et al.. All datasets were imputed separately using SHAPEIT v2.837 and IMPUTE v2.3.2 using a merged reference panel consisting of data from phase three of the 1,000 genomes project and the UK10K–.TCGA cases were genotyped on the Affymetrix Genomewide 6 […]

library_books

Genome wide association study in 176,678 Europeans reveals genetic loci for tanning response to sun exposure

2018
Nat Commun
PMCID: 5940788
PMID: 29739929
DOI: 10.1038/s41467-018-04086-y

[…] grated Release Version 5 (2010–11 data freeze, 2012-03-14 haplotypes) as reference panels. Specifically, SNP genotypes were imputed in two steps. First, genotypes on each chromosome were phased using ShapeIT (v2.r837). Then, phased data were submitted to the Michigan Imputation Server, and imputed using Minimac3. The protocol of the study was approved by the Institutional Review Board of Brigham a […]

call_split

Gene based analysis of genes related to neurotrophic pathway suggests association of BDNF and VEGFA with antidepressant treatment response in depressed patients

2018
Sci Rep
PMCID: 5934385
PMID: 29725086
DOI: 10.1038/s41598-018-25529-y
call_split See protocol

[…] with haplotype reference panels released in March/April 2012 from the 1000 Genomes Project on the basis of HapMap build 37 (https://mathgen.stats.ox.ac.uk/impute/data_download_1000G_phase1_integrated_SHAPEIT2.html). Only imputed SNPs with high genotype information content (i.e. IMPUTE info score > 0.5) were used in association analyses. In total, 30,040,257 SNPs were imputed with high confidence f […]

call_split

Meta analysis of GWAS on both Chinese and European populations identifies GPR173 as a novel X chromosome susceptibility gene for SLE

2018
PMCID: 5934841
PMID: 29724251
DOI: 10.1186/s13075-018-1590-3
call_split See protocol

[…] On the basis of genotyping data, we imputed the X chromosome SNPs for all three datasets. First, SHAPEIT [] was used to prephase each of the datasets. Subsequently, in order to obtain genotypes of additional SNPs, imputation on X chromosome SNPs was performed using IMPUTE v2.3.2 [] on the three s […]

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SHAPEIT institution(s)
Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland; Swiss Institute of Bioinformatics (SIB), University of Geneva, Geneva, Switzerland; Institute of Genetics and Genomics in Geneva, University of Geneva, Geneva, Switzerland; Chaire de Bioinformatique, Conservatoire National des Arts et Métiers, Paris, France; Department of Statistics, University of Oxford, Oxford, UK
SHAPEIT funding source(s)
Supported by a Swiss National Science Foundation (SNSF) project grant (PP00P3_176977), a Swiss National Science Foundation (SNSF) project grant (31003A-179380) and by core funding from the University of Lausanne, the European Research Council (ERC; grant 617306), the Louis-Jeantet Foundation, European Research Council and Swiss National Science Foundation.

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