Scedar: A scalable Python']Python package for single-cell RNA-seq exploratory data analysis

被引:7
|
作者
Zhang, Yuanchao [1 ,2 ]
Kim, Man S. [1 ]
Reichenberger, Erin R. [1 ]
Stear, Ben [1 ]
Taylor, Deanne M. [1 ,3 ]
机构
[1] Childrens Hosp Philadelphia, Dept Biomed & Hlth Informat, Philadelphia, PA 19104 USA
[2] Rutgers State Univ, Dept Genet, Piscataway, NJ USA
[3] Univ Penn, Dept Pediat, Perelman Sch Med, Philadelphia, PA 19104 USA
关键词
EXPRESSION; GENE; HETEROGENEITY; STATES;
D O I
10.1371/journal.pcbi.1007794
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
In single-cell RNA-seq (scRNA-seq) experiments, the number of individual cells has increased exponentially, and the sequencing depth of each cell has decreased significantly. As a result, analyzing scRNA-seq data requires extensive considerations of program efficiency and method selection. In order to reduce the complexity of scRNA-seq data analysis, we present scedar, a scalable Python package for scRNA-seq exploratory data analysis. The package provides a convenient and reliable interface for performing visualization, imputation of gene dropouts, detection of rare transcriptomic profiles, and clustering on large-scale scRNA-seq datasets. The analytical methods are efficient, and they also do not assume that the data follow certain statistical distributions. The package is extensible and modular, which would facilitate the further development of functionalities for future requirements with the open-source development community. The scedar package is distributed under the terms of the MIT license at https://pypi.org/project/scedar..
引用
收藏
页数:24
相关论文
共 50 条
  • [1] pyrpipe: a Python']Python package for RNA-Seq workflows
    Singh, Urminder
    Li, Jing
    Seetharam, Arun
    Wurtele, Eve Syrkin
    [J]. NAR GENOMICS AND BIOINFORMATICS, 2021, 3 (02) : 1 - 8
  • [2] scFates: a scalable python']python package for advanced pseudotime and bifurcation analysis from single-cell data
    Faure, Louis
    Soldatov, Ruslan
    Kharchenko, Peter, V
    Adameyko, Igor
    [J]. BIOINFORMATICS, 2023, 39 (01)
  • [3] Sciviewer enables interactive visual interrogation of single-cell RNA-Seq data from the Python']Python programming environment
    Kotliar, Dylan
    Colubri, Andres
    [J]. BIOINFORMATICS, 2021, 37 (21) : 3961 - 3963
  • [4] ascend: R package for analysis of single-cell RNA-seq data
    Senabouth, Anne
    Lukowski, Samuel W.
    Hernandez, Jose Alquicira
    Andersen, Stacey B.
    Mei, Xin
    Nguyen, Quan H.
    Powell, Joseph E.
    [J]. GIGASCIENCE, 2019, 8 (08):
  • [5] PyDESeq2: a python']python package for bulk RNA-seq differential expression analysis
    Muzellec, Boris
    Telenczuk, Maria
    Cabeli, Vincent
    Andreux, Mathieu
    [J]. BIOINFORMATICS, 2023, 39 (09)
  • [6] PsiNorm: a scalable normalization for single-cell RNA-seq data
    Borella, Matteo
    Martello, Graziano
    Risso, Davide
    Romualdi, Chiara
    [J]. BIOINFORMATICS, 2022, 38 (01) : 164 - 172
  • [7] PyLiger: scalable single-cell multi-omic data integration in Python']Python
    Lu, Lu
    Welch, Joshua D.
    [J]. BIOINFORMATICS, 2022, 38 (10) : 2946 - 2948
  • [8] oggmap: a Python']Python package to extract gene ages per orthogroup and link them with single-cell RNA data
    Ullrich, Kristian K.
    Glytnasi, Nikoleta E.
    [J]. BIOINFORMATICS, 2023, 39 (11)
  • [9] A Python']Python library for probabilistic analysis of single-cell omics data
    Gayoso, Adam
    Lopez, Romain
    Xing, Galen
    Boyeau, Pierre
    Amiri, Valeh Valiollah Pour
    Hong, Justin
    Wu, Katherine
    Jayasuriya, Michael
    Mehlman, Edouard
    Langevin, Maxime
    Liu, Yining
    Samaran, Jules
    Misrachi, Gabriel
    Nazaret, Achille
    Clivio, Oscar
    Xu, Chenling
    Ashuach, Tal
    Gabitto, Mariano
    Lotfollahi, Mohammad
    Svensson, Valentine
    Beltrame, Eduardo da Veiga
    Kleshchevnikov, Vitalii
    Talavera-Lopez, Carlos
    Pachter, Lior
    Theis, Fabian J.
    Streets, Aaron
    Jordan, Michael I.
    Regier, Jeffrey
    Yosef, Nir
    [J]. NATURE BIOTECHNOLOGY, 2022, 40 (02) : 163 - 166
  • [10] scCancer: a package for automated processing of single-cell RNA-seq data in cancer
    Guo, Wenbo
    Wang, Dongfang
    Wang, Shicheng
    Shan, Yiran
    Liu, Changyi
    Gu, Jin
    [J]. BRIEFINGS IN BIOINFORMATICS, 2021, 22 (03)