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Items: 1 to 20 of 102

1.

Cell composition analysis of bulk genomics using single-cell data.

Frishberg A, Peshes-Yaloz N, Cohn O, Rosentul D, Steuerman Y, Valadarsky L, Yankovitz G, Mandelboim M, Iraqi FA, Amit I, Mayo L, Bacharach E, Gat-Viks I.

Nat Methods. 2019 Apr;16(4):327-332. doi: 10.1038/s41592-019-0355-5. Epub 2019 Mar 18.

2.

Pseudotime Reconstruction Using TSCAN.

Ji Z, Ji H.

Methods Mol Biol. 2019;1935:115-124. doi: 10.1007/978-1-4939-9057-3_8.

PMID:
30758823
3.

A component overlapping attribute clustering (COAC) algorithm for single-cell RNA sequencing data analysis and potential pathobiological implications.

Peng H, Zeng X, Zhou Y, Zhang D, Nussinov R, Cheng F.

PLoS Comput Biol. 2019 Feb 19;15(2):e1006772. doi: 10.1371/journal.pcbi.1006772. eCollection 2019 Feb.

4.

A multitask clustering approach for single-cell RNA-seq analysis in Recessive Dystrophic Epidermolysis Bullosa.

Zhang H, Lee CAA, Li Z, Garbe JR, Eide CR, Petegrosso R, Kuang R, Tolar J.

PLoS Comput Biol. 2018 Apr 9;14(4):e1006053. doi: 10.1371/journal.pcbi.1006053. eCollection 2018 Apr.

5.

Data Analysis in Single-Cell Transcriptome Sequencing.

Gao S.

Methods Mol Biol. 2018;1754:311-326. doi: 10.1007/978-1-4939-7717-8_18.

PMID:
29536451
6.

scNPF: an integrative framework assisted by network propagation and network fusion for preprocessing of single-cell RNA-seq data.

Ye W, Ji G, Ye P, Long Y, Xiao X, Li S, Su Y, Wu X.

BMC Genomics. 2019 May 8;20(1):347. doi: 10.1186/s12864-019-5747-5.

7.

A Bayesian mixture model for clustering droplet-based single-cell transcriptomic data from population studies.

Sun Z, Chen L, Xin H, Jiang Y, Huang Q, Cillo AR, Tabib T, Kolls JK, Bruno TC, Lafyatis R, Vignali DAA, Chen K, Ding Y, Hu M, Chen W.

Nat Commun. 2019 Apr 9;10(1):1649. doi: 10.1038/s41467-019-09639-3.

8.

SINCERA: A Pipeline for Single-Cell RNA-Seq Profiling Analysis.

Guo M, Wang H, Potter SS, Whitsett JA, Xu Y.

PLoS Comput Biol. 2015 Nov 24;11(11):e1004575. doi: 10.1371/journal.pcbi.1004575. eCollection 2015 Nov.

9.

The promise of single-cell RNA sequencing for kidney disease investigation.

Wu H, Humphreys BD.

Kidney Int. 2017 Dec;92(6):1334-1342. doi: 10.1016/j.kint.2017.06.033. Epub 2017 Oct 12. Review.

10.

Recovery and analysis of transcriptome subsets from pooled single-cell RNA-seq libraries.

Riemondy KA, Ransom M, Alderman C, Gillen AE, Fu R, Finlay-Schultz J, Kirkpatrick GD, Di Paola J, Kabos P, Sartorius CA, Hesselberth JR.

Nucleic Acids Res. 2019 Feb 28;47(4):e20. doi: 10.1093/nar/gky1204.

11.

JingleBells: A Repository of Immune-Related Single-Cell RNA-Sequencing Datasets.

Ner-Gaon H, Melchior A, Golan N, Ben-Haim Y, Shay T.

J Immunol. 2017 May 1;198(9):3375-3379. doi: 10.4049/jimmunol.1700272.

12.
13.

scruff: an R/Bioconductor package for preprocessing single-cell RNA-sequencing data.

Wang Z, Hu J, Johnson WE, Campbell JD.

BMC Bioinformatics. 2019 May 2;20(1):222. doi: 10.1186/s12859-019-2797-2.

14.

ASAP: a web-based platform for the analysis and interactive visualization of single-cell RNA-seq data.

Gardeux V, David FPA, Shajkofci A, Schwalie PC, Deplancke B.

Bioinformatics. 2017 Oct 1;33(19):3123-3125. doi: 10.1093/bioinformatics/btx337.

15.

Analysis of Technical and Biological Variability in Single-Cell RNA Sequencing.

Kim B, Lee E, Kim JK.

Methods Mol Biol. 2019;1935:25-43. doi: 10.1007/978-1-4939-9057-3_3.

PMID:
30758818
16.

A statistical approach for identifying differential distributions in single-cell RNA-seq experiments.

Korthauer KD, Chu LF, Newton MA, Li Y, Thomson J, Stewart R, Kendziorski C.

Genome Biol. 2016 Oct 25;17(1):222.

17.

Analysis of EBV Transcription Using High-Throughput RNA Sequencing.

O'Grady T, Baddoo M, Flemington EK.

Methods Mol Biol. 2017;1532:105-121.

18.

Inference of differentiation time for single cell transcriptomes using cell population reference data.

Sun N, Yu X, Li F, Liu D, Suo S, Chen W, Chen S, Song L, Green CD, McDermott J, Shen Q, Jing N, Han JJ.

Nat Commun. 2017 Nov 30;8(1):1856. doi: 10.1038/s41467-017-01860-2.

19.

Bias, robustness and scalability in single-cell differential expression analysis.

Soneson C, Robinson MD.

Nat Methods. 2018 Apr;15(4):255-261. doi: 10.1038/nmeth.4612. Epub 2018 Feb 26.

PMID:
29481549
20.

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