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Information


Unique identifier OMICS_11224
Name Pascal
Alternative name Pathway scoring algorithm
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS
Programming languages Java
Computer skills Advanced
Stability Stable
Maintained Yes

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Maintainer


  • person_outline Sven Bergmann

Publication for Pathway scoring algorithm

Pascal citations

 (11)
library_books

A sibling method for identifying vQTLs

2018
PLoS One
PMCID: 5884517
PMID: 29617452
DOI: 10.1371/journal.pone.0194541

[…] n addition to investigating the gene function for the replicated SNP, we also performed two analyses that pool SNPs: gene-based and pathway-based pooling (see ). For the gene analysis, we found using PASCAL that the gene on which the significant SNP for BMI variability was located (MAST4) was significantly enriched (p = 0.0015 in the FHS data; p = 0.1 in the replication data). Table I in shows ot […]

library_books

The integrated landscape of causal genes and pathways in schizophrenia

2018
PMCID: 5851982
PMID: 29540662
DOI: 10.1038/s41398-018-0114-x

[…] integrated with tissue-specific networks to predict the potential causal genes. In this study, we first converted SNP-based summary statistics (SNP P values from PGC2) into gene-based P values using Pascal. The gene-level P values were then used as input for NetWAS, and brain-specific functional interaction networks were selected. More detailed information about tissue-specific networks and NetWA […]

library_books

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease

2018
PLoS Comput Biol
PMCID: 5849332
PMID: 29494619
DOI: 10.1371/journal.pcbi.1005934

[…] ough many coexpressed regulatory regions are not promoters for annotated genes (supplementary results; ), we compared the named genes in our results with gene-level burden of significance scores from PASCAL[] analysis of the original GWAS studies. Since the coexpressed regulatory regions were detected due to the presence of a variant with a low p-value, it is expected that the genes with coexpress […]

library_books

Bayesian association scan reveals loci associated with human lifespan and linked biomarkers

2017
Nat Commun
PMCID: 5537485
PMID: 28748955
DOI: 10.1038/ncomms15842

[…] er published longevity GWAS, we had low power to replicate our findings. Despite this fact many of the discovered loci replicated in independent data sets. We performed pathway enrichment analysis by PASCAL using the BF permutation-based P values (). Only the lipoprotein metabolism pathway and lipid digestion, mobilization and transport showed statistically significant enrichment (P=3.1 × 10−6, 1. […]

library_books

Network assisted analysis of GWAS data identifies a functionally relevant gene module for childhood onset asthma

2017
Sci Rep
PMCID: 5430538
PMID: 28428554
DOI: 10.1038/s41598-017-01058-y

[…] study included a novel, exact and efficient algorithm to compute gene-level P-values from SNP-level P-values. Although other existing methods also allow such computation, including VEGAS2, MAGMA and PASCAL, these methods use raw genotype data, or an external reference SNP panel (e.g., Hapamap2 or 1000 Genomes panel) when the original genotype data are unavailable, to compute the correlation among […]

library_books

Analysis of the human monocyte derived macrophage transcriptome and response to lipopolysaccharide provides new insights into genetic aetiology of inflammatory bowel disease

2017
PLoS Genet
PMCID: 5358891
PMID: 28263993
DOI: 10.1371/journal.pgen.1006641

[…] lik-Sullivan et al [] using the same summary p-value data that we use here. The ratio of observed:expected ratio was plotted for each bin (). Summary p-values for this set of loci were computed using PASCAL [] to calculate the total “burden of significance” within a range of +/-100kb from each TSS region, for each GWAS study, and then to quantify the probability of such a signal arising by chance […]

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Pascal institution(s)
Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
Pascal funding source(s)
Supported by research grants from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, the Swiss National Science Foundation (grants 33CSCO122661, 33CS30-139468 and 33CS30-148401), the Leenaards Foundation, the Swiss Institute of Bioinformatics, the Swiss National Science Foundation (31003A143914, 51RTP0_151019), the Swiss Institute of Bioinformatics, the Swiss National Science Foundation (grant FN 310030_152724 / 1) and SystemsX.ch through the SysGenetiX project.

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