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ZIFA specifications

Information


Unique identifier OMICS_08437
Name ZIFA
Alternative name Zero Inflated Factor Analysis
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python
License MIT License
Computer skills Advanced
Stability Stable
Requirements
pylab, scipy, numpy, scikits.learn
Maintained Yes

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Documentation


Maintainer


  • person_outline Emma Pierson

Publication for Zero Inflated Factor Analysis

ZIFA citations

 (9)
library_books

Delineating biological and technical variance in single cell expression data

2017
PMCID: 5608017
PMID: 28716546
DOI: 10.1016/j.biocel.2017.07.006

[…] features of low quality cells (). The methods developed to identify sub-populations, including the popular principal component analysis (PCA), t-distributed stochastic neighbour embedding (t-SNE), or zero-inflated factor analysis (ZIFA) () are also used to filter low quality cells. However, comprehensive quality controls with more than one metric are more effective for discarding true low quality […]

library_books

Using neural networks for reducing the dimensions of single cell RNA Seq data

2017
Nucleic Acids Res
PMCID: 5737331
PMID: 28973464
DOI: 10.1093/nar/gkx681

[…] sters them using graph based methods. SNN-Cliq sometimes generates error messages when the number of cell types (k) is 2, so we left it out in this comparison. We also tried to compare our results to ZIFA. However, ZIFA did not finish after running for two days when trying to cluster 300 cells with 9437 expression values each. To improve its run time we reduced the number of genes to 1356 (selecti […]

library_books

Computational approaches for interpreting scRNA‐seq data

2017
FEBS Lett
PMCID: 5575496
PMID: 28524227
DOI: 10.1002/1873-3468.12684

[…] tion scLVM, single‐cell latent variable model scRNA‐seq, single‐cell RNA sequencing SNN, shared nearest neighbour UMIs, unique molecular identifiers WGCNA, weighted gene coexpression network analysis ZIFA, zero‐inflated factor analysis […]

library_books

Single cell RNA sequencing of the brain

2017
PMCID: 5465230
PMID: 28597408
DOI: 10.1186/s40169-017-0150-9

[…] genes []. More sophisticated machine learning methods have been used to overcome the limitations in conventional methods due to the frequency of genes with zero counts. An interesting example is the zero inflated factor analysis (ZIFA), which implements a dimension-reduction approach and uses a latent variable factor model to accommodate zeros [].The majority of computational methods for subpopul […]

call_split

CIDR: Ultrafast and accurate clustering through imputation for single cell RNA seq data

2017
Genome Biol
PMCID: 5371246
PMID: 28351406
DOI: 10.1186/s13059-017-1188-0
call_split See protocol

[…] CIDR. For the other dimensionality-reduction and clustering algorithms, rows with tag sums less than or equal to 10 were deleted. Log tags, with base 2 and prior count 1, were used as the inputs for ZIFA, as suggested by the ZIFA documentation. Data sets transformed by logTPM were used as inputs for prcomp and t-SNE. […]

library_books

Single Cell Transcriptomics Bioinformatics and Computational Challenges

2016
Front Genet
PMCID: 5030210
PMID: 27708664
DOI: 10.3389/fgene.2016.00163

[…] in the order of dimension reduction, clustering, and other clustering variant methods. The datasets that were used to test these algorithms are listed in Table .Among the dimension reduction methods, Zero-inflated factor analysis (ZIFA) algorithm is a new method that includes dropout events by representing the probability of gene dropout as an exponential function of its mean expression (Pierson a […]

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ZIFA institution(s)
Department of Statistics, University of Oxford, Oxford, UK

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