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BASiCS specifications

Information


Unique identifier OMICS_09027
Name BASiCS
Alternative name Bayesian Analysis of Single-Cell Sequencing data
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
Computer skills Advanced
Stability Stable
Maintained Yes

Versioning


No version available

Documentation


Maintainers


  • person_outline Catalina A. Vallejos
  • person_outline Nils Eling

Publications for Bayesian Analysis of Single-Cell Sequencing data

BASiCS citations

 (9)
library_books

Meet U: Educating through research immersion

2018
PLoS Comput Biol
PMCID: 5854232
PMID: 29543809
DOI: 10.1371/journal.pcbi.1005992

[…] onomeric partners (, top green panel). Prior to the course, they had some basic to intermediate programming experience, and their knowledge in structural bioinformatics ranged from very little to the basics of protein structure determination and modeling. At the end of the course, all 6 teams managed to deliver a finalized end product, and some of the results were comparable to those of state-of-t […]

library_books

Whole Body Single Cell Sequencing Reveals Transcriptional Domains in the Annelid Larval Body

2018
Mol Biol Evol
PMCID: 5913682
PMID: 29373712
DOI: 10.1093/molbev/msx336

[…] The BASiCS package () was used to normalize read counts by incorporating ERCC spike-ins for technical noise estimation. Specific ERCC spike-ins were removed if not detected in the data set. Posterior esti […]

library_books

Computational approaches for interpreting scRNA‐seq data

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

[…] esented a statistical framework to decompose the total variance into the technical and biological variance based on a generative model, which would help in identifying variable genes. Another method, BASiCS, uses a Bayesian model which jointly models spike‐ins and endogenous genes and provides posterior distributions for the extent of biological variability . […]

library_books

Single Cell RNA Sequencing: Assessment of Differential Expression Analysis Methods

2017
Front Genet
PMCID: 5440469
PMID: 28588607
DOI: 10.3389/fgene.2017.00062

[…] explicitly modeling the multimodal distributions of single cells and testing for differentially distributed genes associated with this multimodality. Bayesian Analysis of Single-Cell Sequencing Data, BASiCS (Vallejos et al., ), estimates the normalization parameters jointly across all genes by modeling spike-ins and endogenous genes as two Poisson-Gamma hierarchical models with shared parameters, […]

library_books

Computational Approaches to Chemical Hazard Assessment

2017
ALTEX
PMCID: 5848496
PMID: 29101769
DOI: 10.14573/altex.1710141

[…] roach, as Arthur Conan Doyle stated “It is a capital mistake to theorize before one has data. Insensibly, one begins to twist the facts to suit theories, instead of theories to suit facts”. Here, the basics of these approaches have been discussed.This is not arguing for a blind belief in such statistical evaluation of data. To quote Alvin Toffler (1928-2016): “You can use all the quantitative data […]

call_split

Intrinsic transcriptional heterogeneity in B cells controls early class switching to IgE

2017
PMCID: 5206502
PMID: 27994069
DOI: 10.1084/jem.20161056
call_split See protocol

[…] 1 or G2M score was above 0.5, the cell was assigned to the stage with the highest score. If neither of these scores was above 0.5, the cell was assigned to S phase.HVGs and LVGs were determined using BASiCs (data as described in ). Estimated read counts from Salmon (rounded to integer values) were used as input. HVGs were detected at a variance contribution threshold of 89% leading to an optimized […]

Citations

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BASiCS institution(s)
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, UK; Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK; Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; MRC Biostatistics Unit, University of Cambridge, Cambridge Institute of Public Health, Forvie Site, Cambridge Biomedical Campus, Cambridge, UK; The Alan Turing Institute, British Library, London, UK; Department of Statistical Science, University College London, London, UK
BASiCS funding source(s)
Supported by the European Molecular Biology Laboratory (EMBL) international PhD programme, the MRC Skills Development Fellowship (MR/P014178/1), a MRC grant MC_UP_0801/1, a core support of Cancer Research UK, EMBL, The Alan Turing Institute and EPSRC grant EP/N510129/1.

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