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FlashPCA specifications


Unique identifier OMICS_14559
Name FlashPCA
Alternative name Flash principal component analysis
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input format BED, BIM, FAM
Output data A top k eigenvectors of the covariance X XT/p, a top k principal components, a top k eigenvalues of X XT/p and the proportion of total variance.
Output format TXT
Operating system Unix/Linux, Mac OS
Programming languages C++, R
License GNU General Public License version 3.0
Computer skills Advanced
Version 2.0
Stability Stable
g++ compiler, Eigen, Spectra, Boost, libgomp, plink, Homebrew, clang C++ compiler
Maintained Yes




No version available



  • person_outline Gad Abraham

Publications for Flash principal component analysis

FlashPCA citations


Item level analyses reveal genetic heterogeneity in neuroticism

Nat Commun
PMCID: 5834468
PMID: 29500382
DOI: 10.1038/s41467-018-03242-8

[…] subjects in sample 2. Additionally, we included the first 10 genetic PCs as covariates to control for potential population stratification. Genetic PCs were computed separately for both samples using FlashPCA 2 on individuals of European ancestry, after LD pruning and filtering out SNPs with MAF < 0.01 and genotype missingness > 0.05.Final data analysis was restricted to autosomal, bi-allelic SNPs […]


Human longevity: 25 genetic loci associated in 389,166 UK biobank participants

PMCID: 5764389
PMID: 29227965
DOI: 10.18632/aging.101334

[…] rectly-genotyped data we used Plink (v1.9) [] in linear (additive) or binary (fisher) models, as appropriate, adjusted for the same covariates as above including the first 5 principal components from FlashPCA. […]


Red blood cell distribution width: Genetic evidence for aging pathways in 116,666 volunteers

PLoS One
PMCID: 5619771
PMID: 28957414
DOI: 10.1371/journal.pone.0185083

[…] e model. For X, Y and mitochondrial variants we used Plink (v1.9) [] to determine the associations between genotype and phenotype, with additional adjustment for the first 5 principal components from FlashPCA [] based on 95,535 independent SNPs (pairwise r2<0.1) with MAF >2.5%, missingness <1.5%, and HWE p>1x10-6.The main outcome of the GWAS was RDW residuals from a linear regression model adjuste […]


Genomic signatures of adaptive introgression from European mouflon into domestic sheep

Sci Rep
PMCID: 5548776
PMID: 28790322
DOI: 10.1038/s41598-017-07382-7

[…] and using supervised ancestry assignments (Supplementary Text ). A principal component analysis (PCA) was performed to investigate the ordinal relationships between populations and individuals, using flashpca v1.2 with default settings. Neighbour-net graphs using Reynolds’ distances, calculated with a custom script, were generated using Splitstree v4.13.1. The occurrence of admixture was further i […]


An interaction map of circulating metabolites, immune gene networks, and their genetic regulation

Genome Biol
PMCID: 5540552
PMID: 28764798
DOI: 10.1186/s13059-017-1279-y

[…] . Models were adjusted for age, sex, and the first ten genetic principal components (PCs). Genetic PCs were generated from a linkage-disequilibrium (LD) pruned set of approximately 200,000 SNPs using flashpca []. P values for each association in DILGOM07 and YFS were combined in a meta-analysis using the METAL software [], which implements a sample size weighted Z-score method. A SNP was considere […]


Structural variants in genes associated with human Williams Beuren syndrome underlie stereotypical hypersociability in domestic dogs

Sci Adv
PMCID: 5517105
PMID: 28776031
DOI: 10.1126/sciadv.1700398

[…] cluded for all downstream analyses. We used PLINK to obtain a pruned set of 25,510 uncorrelated and unlinked SNPs with the argument --indep-pairwise 50 5 0.2 and then conducted a PCA with the program flashPCA (fig. S7) (). We also conducted a binary association test in PLINK on the binary phenotype of species membership. Further, we conducted a quantitative association test using the quantitative […]


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FlashPCA institution(s)
Centre for Systems Genomics, School of BioSciences, University of Melbourne, Parkville, VIC, Australia; Department of Pathology, University of Melbourne, Parkville, VIC, Australia; Department of Statistics, Purdue University, West Lafayette, IN, USA
FlashPCA funding source(s)
This work was supported by a National Health and Medical Research Council Early Career Fellowship (NHMRC) no. 1090462, an NHMRC and Australian Heart Foundation Career Development Fellowship no. 1061435.

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