scTIM: seeking cell-type-indicative marker from single cell RNA-seq data by consensus optimization
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
scTIM: seeking cell-type-indicative marker from single cell RNA-seq data by consensus optimization
Authors
Keywords
-
Journal
BIOINFORMATICS
Volume -, Issue -, Pages -
Publisher
Oxford University Press (OUP)
Online
2019-12-13
DOI
10.1093/bioinformatics/btz936
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Publisher Correction: Challenges in unsupervised clustering of single-cell RNA-seq data
- (2019) Vladimir Yu Kiselev et al. NATURE REVIEWS GENETICS
- DEsingle for detecting three types of differential expression in single-cell RNA-seq data
- (2018) Zhun Miao et al. BIOINFORMATICS
- Mapping the Mouse Cell Atlas by Microwell-Seq
- (2018) Xiaoping Han et al. CELL
- M3Drop: dropout-based feature selection for scRNASeq
- (2018) Tallulah S Andrews et al. BIOINFORMATICS
- VASC: Dimension Reduction and Visualization of Single-cell RNA-seq Data by Deep Variational Autoencoder
- (2018) Dongfang Wang et al. GENOMICS PROTEOMICS & BIOINFORMATICS
- pcaReduce: hierarchical clustering of single cell transcriptional profiles
- (2016) Justina žurauskienė et al. BMC BIOINFORMATICS
- Detection of high variability in gene expression from single-cell RNA-seq profiling
- (2016) Hung-I Harry Chen et al. BMC GENOMICS
- Dissecting direct reprogramming from fibroblast to neuron using single-cell RNA-seq
- (2016) Barbara Treutlein et al. NATURE
- A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages
- (2016) Robert J. Kimmerling et al. Nature Communications
- Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets
- (2015) Evan Z. Macosko et al. CELL
- Meta- and Orthogonal Integration of Influenza “OMICs” Data Defines a Role for UBR4 in Virus Budding
- (2015) Shashank Tripathi et al. Cell Host & Microbe
- limma powers differential expression analyses for RNA-sequencing and microarray studies
- (2015) Matthew E. Ritchie et al. NUCLEIC ACIDS RESEARCH
- BASiCS: Bayesian Analysis of Single-Cell Sequencing Data
- (2015) Catalina A. Vallejos et al. PLoS Computational Biology
- Single cell dissection of early kidney development: multilineage priming
- (2014) E. W. Brunskill et al. DEVELOPMENT
- Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq
- (2014) Barbara Treutlein et al. NATURE
- Single-cell RNA-seq reveals dynamic paracrine control of cellular variation
- (2014) Alex K. Shalek et al. NATURE
- MSMBvariation and prostate cancer risk: Clues towards a possible fungal etiology
- (2014) Siobhan Sutcliffe et al. PROSTATE
- Single-Cell RNA-Seq Reveals Dynamic, Random Monoallelic Gene Expression in Mammalian Cells
- (2014) Q. Deng et al. SCIENCE
- Accounting for technical noise in single-cell RNA-seq experiments
- (2013) Philip Brennecke et al. NATURE METHODS
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now