Ecosyste.ms: Papers

An open API service providing mapping between scientific papers and software projects that are mentioned in them.
All mentions data is based on the CZI Software Mentions dataset.

Projects: pypi: scLVM

https://packages.ecosyste.ms/registries/pypi.org/packages/scLVM

scLVM
8 versions
Latest release: over 7 years ago
16 downloads last month

Papers Mentioning scLVM 19

10.15252/msb.20188746
Current best practices in single‐cell RNA‐seq analysis: a tutorial
Cited by: 1,173
Author(s): Malte D. Luecken, Fabian J. Theis
Software Mentions: 20
Published: over 5 years ago
10.3389/fgene.2016.00163
Single-Cell Transcriptomics Bioinformatics and Computational Challenges
Cited by: 101
Author(s): Olivier Poirion, Xun Zhu, Travers Ching, Lana X. Garmire
Software Mentions: 15
Published: about 8 years ago
10.1186/s13059-016-0927-y
Design and computational analysis of single-cell RNA-sequencing experiments
Cited by: 409
Author(s): Rhonda Bacher, Christina Kendziorski
Software Mentions: 10
Published: over 8 years ago
10.7554/eLife.33105
Single-cell RNA-seq reveals hidden transcriptional variation in malaria parasites
Cited by: 152
Author(s): Adam J. Reid, Arthur M. Talman, Hayley M. Bennett, Ana Gomes, Mandy Sanders, Christopher J. R. Illingworth, Oliver Billker, Matthew Berriman, Mara Lawniczak
Software Mentions: 9
Published: over 6 years ago
10.1186/s13059-017-1188-0
CIDR: Ultrafast and accurate clustering through imputation for single-cell RNA-seq data
Cited by: 391
Author(s): Peijie Lin, Michael Troup, Joshua W. K. Ho
Software Mentions: 8
Published: over 7 years ago
10.1371/journal.pcbi.1004575
SINCERA: A Pipeline for Single-Cell RNA-Seq Profiling Analysis
Cited by: 292
Author(s): Minzhe Guo, Hui Wang, S. Steven Potter, Jeffrey A. Whitsett, Yan Xu
Software Mentions: 7
Published: almost 9 years ago
10.7717/peerj.2888
Detecting heterogeneity in single-cell RNA-Seq data by non-negative matrix factorization
Cited by: 67
Author(s): Xun Zhu, Travers Ching, Xinghua Pan, Sherman M. Weissman, Lana X. Garmire
Software Mentions: 7
Published: almost 8 years ago
10.1016/j.stem.2015.04.004
Combined Single-Cell Functional and Gene Expression Analysis Resolves Heterogeneity within Stem Cell Populations
Cited by: 369
Author(s): Nicola K. Wilson, David G. Kent, Florian Buettner, Mona Shehata, Iain C. Macaulay, Fernando J. Calero-Nieto, Manuel Sánchez Castillo, Caroline A. Oedekoven, Evangelia Diamanti, Reiner Schulte, Chris P. Ponting, Thierry Voet, Carlos Caldas, John Stingl, Anthony Green, Fabian J. Theis, Berthold Göttgens
Software Mentions: 5
Published: over 9 years ago
10.1002/1878-0261.12138
<scp>APE</scp>1/Ref‐1 knockdown in pancreatic ductal adenocarcinoma – characterizing gene expression changes and identifying novel pathways using single‐cell <scp>RNA</scp> sequencing
Cited by: 26
Author(s): Fenil Shah, Emery Goossens, Nadia M. Atallah, Michelle Grimard, Mark R. Kelley, Melissa L. Fishel
Software Mentions: 5
Published: about 7 years ago
10.1186/s12859-021-04136-1
scSensitiveGeneDefine: sensitive gene detection in single-cell RNA sequencing data by Shannon entropy
Cited by: 3
Author(s): Zechuan Chen, Zeruo Yang, Xi Yuan, Xiaoming Zhang, Pei Hao
Software Mentions: 4
Published: over 3 years ago
10.1038/s41598-018-35365-9
Detection of correlated hidden factors from single cell transcriptomes using Iteratively Adjusted-SVA (IA-SVA)
Cited by: 7
Author(s): Dong‐Hyung Lee, Anthony Cheng, Nathan Lawlor, Mohan Bolisetty, Duygu Ucar
Software Mentions: 4
Published: about 6 years ago
10.1186/s12915-017-0453-8
Telomere heterogeneity linked to metabolism and pluripotency state revealed by simultaneous analysis of telomere length and RNA-seq in the same human embryonic stem cell
Cited by: 16
Author(s): Hua Wang, Kunshan Zhang, Yifei Liu, Yudong Fu, Shan Gao, Peng Gong, Haiying Wang, Zhongli Zhou, Ming Zeng, Zhenfeng Wu, Yu Sun, Tong Chen, Siguang Li, Lin Liu
Software Mentions: 3
Published: almost 7 years ago
10.1038/s41598-017-19100-4
Single-cell RNA-sequencing resolves self-antigen expression during mTEC development
Cited by: 28
Author(s): Ricardo J. Miragaia, Xiuwei Zhang, Tomás Gomes, Valentine Svensson, Tomislav Ilicic, Johan Henriksson, Gozde Kar, Tapio Lönnberg
Software Mentions: 3
Published: almost 7 years ago
10.1186/s13059-017-1334-8
f-scLVM: scalable and versatile factor analysis for single-cell RNA-seq
Cited by: 102
Author(s): Florian Buettner, Naruemon Pratanwanich, Davis J. McCarthy, John C. Marioni, Oliver Stegle
Software Mentions: 3
Published: about 7 years ago
10.1186/s12859-016-1109-3
SCOUP: a probabilistic model based on the Ornstein–Uhlenbeck process to analyze single-cell expression data during differentiation
Cited by: 49
Author(s): Hirotaka Matsumoto, Hisanori Kiryu
Software Mentions: 3
Published: over 8 years ago
10.1186/s40169-017-0177-y
Using single‐cell multiple omics approaches to resolve tumor heterogeneity
Cited by: 61
Author(s): Michael A. Ortega, Olivier Poirion, Xun Zhu, Sijia Huang, Thomas Wolfgruber, Robert Sebra, Lana X. Garmire
Software Mentions: 2
Published: almost 7 years ago
10.1038/srep33892
Identifying and removing the cell-cycle effect from single-cell RNA-Sequencing data
Cited by: 84
Author(s): Martin Barron, Jun Li
Software Mentions: 2
Published: about 8 years ago
10.1186/s12859-020-03625-z
A robust nonlinear low-dimensional manifold for single cell RNA-seq data
Cited by: 13
Author(s): Archit Verma, Barbara E. Engelhardt
Software Mentions: 2
Published: over 4 years ago
10.1038/s41598-017-13665-w
Controlling for Confounding Effects in Single Cell RNA Sequencing Studies Using both Control and Target Genes
Cited by: 33
Author(s): Mengjie Chen, Xiang Zhou
Software Mentions: 1
Published: about 7 years ago