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BackSPIN specifications

Information


Unique identifier OMICS_10721
Name BackSPIN
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data BackSPIN takes input in CEF format.
Output data It produces an annotated CEF file as output.
Operating system Unix/Linux
Programming languages Python
Computer skills Advanced
Stability Stable
Requirements
Numpy, Scipy, SciKit-learn
Maintained Yes

Versioning


No version available

Documentation


Maintainer


  • person_outline Sten Linnarsson

Publication for BackSPIN

BackSPIN citations

 (11)
library_books

A geometric approach to characterize the functional identity of single cells

2018
Nat Commun
PMCID: 5904143
PMID: 29666373
DOI: 10.1038/s41467-018-03933-2

[…] identified using ACTION, we assigned each cell to a single dominant function, as determined by its closest archetype. We compare our method to five recently proposed methods: Seurat (v2.2), SNNCliq, BackSPIN, single-cell ParTI,, and TSCAN (Supplementary Note ) to predict annotated cell types on the same four datasets (see Methods, Datasets). For the Melanoma dataset, SNNCliq did not terminate aft […]

library_books

Exploring the Complexity of Cortical Development Using Single Cell Transcriptomics

2018
Front Neurosci
PMCID: 5801402
PMID: 29456488
DOI: 10.3389/fnins.2018.00031

[…] (Poirion et al., ). For the unsupervised clustering, ConsensusClusterPlus R (Wilkerson and Hayes, ), EMCluster (Jung et al., ), SC3 (Kiselev et al., ), SNN-Cliq (Xu and Su, ), SCUBA (Marco et al., ), BackSPIN (Zeisel et al., ), and PAGODA (Fan et al., ) provide methods to identify the subpopulation from the single-cell transcriptome profiles. Following clustering, DESeq2 (Love et al., ), SCDE (Kha […]

library_books

Single cell RNA sequencing of the brain

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

[…] ferentiation stages from oligodendrocyte precursor cells to mature oligodendrocytes. The fine differentiation stages were identified using t-SNE for dimensionality reduction and the biclustering tool BackSPIN2 for pseudo-time analysis. Thereby, using scRNA-seq methods, the authors revealed the dynamics of the differentiation and maturation of oligodendrocytes.It is difficult to interrogate the und […]

library_books

Age Related Gene Expression in the Frontal Cortex Suggests Synaptic Function Changes in Specific Inhibitory Neuron Subtypes

2017
PMCID: 5446995
PMID: 28611654
DOI: 10.3389/fnagi.2017.00162

[…] . Expression data (number of molecules per cell) was obtained from the Linnarson lab website). This dataset assayed 3005 cells from the somatosensory (S1) cortex and hippocampus. We used the provided BackSPIN clustering that marked cells as one of seven major classes (“level1class” in data file) and 47 cell subclasses. The seven major classes are named: interneurons, pyramidal SS, pyramidal CA1, o […]

library_books

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

[…] a sets.Another package t-SNE [] is popular among biologists, but it is not designed specifically for scRNA-seq data and does not address the issue of dropouts. Other recently developed tools, such as BackSPIN [], pcaReduce [], SC3 [], SNN-Cliq [], RaceID [], and BISCUIT [], were designed to deal with optimal clustering of single cells into meaningful groups or hierarchies. Like ZIFA, these algorit […]

library_books

Molecular Diversity of Midbrain Development in Mouse, Human, and Stem Cells

2016
Cell
PMCID: 5055122
PMID: 27716510
DOI: 10.1016/j.cell.2016.09.027

[…] h the aim of removing data from both broken cells and doublets that might have gone undetected despite the imaging. We further decided to exclude cells that had inconsistent assignment with different BackSPIN parameters and low molecule count. For the hiPSCs and the hESCs this last step of filtering was not performed since it may introduce bias when estimating the abundance of different kind of ce […]

Citations

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BackSPIN institution(s)
Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden; Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden; Division of Vascular Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden; Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden

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