Computational Systems Biology Methods and Protocols.7z

(nextflipdebug5) #1

  1. Picelli S, Bjorklund AK, Faridani OR, Sagasser
    S, Winberg G, Sandberg R (2013) Smart-
    seq2 for sensitive full-length transcriptome
    profiling in single cells. Nat Methods 10
    (11):1096–1098.https://doi.org/10.1038/
    Nmeth.2639

  2. Sasagawa Y, Nikaido I, Hayashi T, Danno H,
    Uno KD, Imai T, Ueda HR (2017) Quartz-
    Seq: a highly reproducible and sensitive sin-
    gle-cell RNA sequencing method, reveals
    non-genetic gene-expression heterogeneity
    (vol 14: R31, 2013). Genome Biol 18.
    https://doi.org/10.1186/S13059-017-
    1154-X

  3. Nakamura T, Yabuta Y, Okamoto I, Aramaki
    S, Yokobayashi S, Kurimoto K, Sekiguchi K,
    Nakagawa M, Yamamoto T, Saitou M (2015)
    SC3-seq: a method for highly parallel and
    quantitative measurement of single-cell gene
    expression. Nucleic Acids Res 43(9).https://
    doi.org/10.1093/nar/gkv134

  4. Jaitin DA, Kenigsberg E, Keren-Shaul H, Ele-
    fant N, Paul F, Zaretsky I, Mildner A, Cohen
    N, Jung S, Tanay A, Amit I (2014) Massively
    parallel single-cell RNA-seq for marker-free
    decomposition of tissues into cell types. Sci-
    ence 343(6172):776–779.https://doi.org/
    10.1126/science.1247651

  5. Fan HC, Fu GK, Fodor SP (2015) Expression
    profiling. Combinatorial labeling of single
    cells for gene expression cytometry. Science
    347(6222):1258367. https://doi.org/10.
    1126/science.1258367

  6. Macosko EZ, Basu A, Satija R, Nemesh J,
    Shekhar K, Goldman M, Tirosh I, Bialas AR,
    Kamitaki N, Martersteck EM, Trombetta JJ,
    Weitz DA, Sanes JR, Shalek AK, Regev A,
    McCarroll SA (2015) Highly parallel
    genome-wide expression profiling of individ-
    ual cells using nanoliter droplets. Cell 161
    (5):1202–1214.https://doi.org/10.1016/j.
    cell.2015.05.002

  7. Klein AM, Mazutis L, Akartuna I, Tallapra-
    gada N, Veres A, Li V, Peshkin L, Weitz DA,
    Kirschner MW (2015) Droplet barcoding for
    single-cell transcriptomics applied to embry-
    onic stem cells. Cell 161(5):1187–1201.
    https://doi.org/10.1016/j.cell.2015.04.
    044

  8. Fan XY, Zhang XN, Wu XL, Guo HS, Hu YQ,
    Tang FC, Huang YY (2015) Single-cell RNA-
    seq transcriptome analysis of linear and circu-
    lar RNAs in mouse preimplantation embryos.
    Genome Biol 16.https://doi.org/10.1186/
    S13059-015-0706-1

  9. Kang Y, Norris MH, Zarzycki-Siek J, Nier-
    man WC, Donachie SP, Hoang TT (2011)
    Transcript amplification from single


bacterium for transcriptome analysis. Genome
Res 21(6):925–935. https://doi.org/10.
1101/gr.116103.110


  1. Kolodziejczyk AA, Kim JK, Svensson V, Mar-
    ioni JC, Teichmann SA (2015) The technol-
    ogy and biology of single-cell RNA
    sequencing. Mol Cell 58(4):610–620.
    https://doi.org/10.1016/j.molcel.2015.04.
    005

  2. Ziegenhain C, Vieth B, Parekh S, Reinius B,
    Guillaumet-Adkins A, Smets M, Leonhardt
    H, Heyn H, Hellmann I, Enard W (2017)
    Comparative analysis of single-cell RNA
    sequencing methods. Mol Cell 65
    (4):631–643. https://doi.org/10.1016/j.
    molcel.2017.01.023

  3. Svensson V, Natarajan KN, Ly LH, Miragaia
    RJ, Labalette C, Macaulay IC, Cvejic A,
    Teichmann SA (2017) Power analysis of sin-
    gle-cell RNA-sequencing experiments. Nat
    Methods 14(4):381–387. https://doi.org/
    10.1038/nmeth.4220

  4. Clark SJ, Lee HJ, Smallwood SA, Kelsey G,
    Reik W (2016) Single-cell epigenomics: pow-
    erful new methods for understanding gene
    regulation and cell identity. Genome Biol 17.
    https://doi.org/10.1186/s13059-016-
    0944-x

  5. Plongthongkum N, Diep DH, Zhang K
    (2014) Advances in the profiling of DNA
    modifications: cytosine methylation and
    beyond. Nat Rev Genet 15(10):647–661.
    https://doi.org/10.1038/nrg3772

  6. Smallwood SA, Lee HJ, Angermueller C,
    Krueger F, Saadeh H, Peet J, Andrews SR,
    Stegle O, Reik W, Kelsey G (2014) Single-
    cell genome-wide bisulfite sequencing for
    assessing epigenetic heterogeneity. Nat Meth-
    ods 11(8):817–820. https://doi.org/10.
    1038/Nmeth.3035

  7. Guo HS, Zhu P, Wu XL, Li XL, Wen L, Tang
    FC (2013) Single-cell methylome landscapes
    of mouse embryonic stem cells and early
    embryos analyzed using reduced representa-
    tion bisulfite sequencing. Genome Res 23
    (12):2126–2135.https://doi.org/10.1101/
    gr.161679.113

  8. Miura F, Enomoto Y, Dairiki R, Ito T (2012)
    Amplification-free whole-genome bisulfite
    sequencing by post-bisulfite adaptor tagging.
    Nucleic Acids Res 40(17).https://doi.org/
    10.1093/nar/gks454

  9. Farlik M, Sheffield NC, Nuzzo A, Datlinger P,
    Schonegger A, Klughammer J, Bock C (2015)
    Single-cell DNA methylome sequencing and
    bioinformatic inference of epigenomic cell-
    state dynamics. Cell Rep 10(8):1386–1397.


366 Yungang Xu and Xiaobo Zhou

Free download pdf