% Chen X, Litzenburger UM, Wei Y, Schep AN, LaGory EL, Choudhry H, Giaccia AJ, Greenleaf WJ, Chang HY. 2018. Joint single-cell DNA accessibility and protein epitope profiling reveals environmental regulation of epigenomic heterogeneity. \textit{Nat Commun} \textbf{9}(1):4590. % doi: 10.1038/s41467-018-07115-y. % Pi-ATAC
% Liu L, Liu C, Quintero A, Wu L, Yuan Y, Wang M, Cheng M, Leng L, Xu L, Dong G, Li R, Liu Y, Wei X, Xu J, Chen X, Lu H, Chen D, Wang Q, Zhou Q, Lin X, Li G, Liu S, Wang Q, Wang H, Fink JL, Gao Z, Liu X, Hou Y, Zhu S, Yang H, Ye Y, Lin G, Chen F, Herrmann C, Eils R, Shang Z, Xu X. 2019. Deconvolution of single-cell multi-omics layers reveals regulatory heterogeneity. \textit{Nat Commun} \textbf{10}(1):470. % scCAT-seq
% Cao J, Packer JS, Ramani V, Cusanovich DA, Huynh C, Daza R, Qiu X, Lee C, Furlan SN, Steemers FJ, Adey A, Waterston RH, Trapnell C, Shendure J. 2017. Comprehensive single-cell transcriptional profiling of a multicellular organism. \textit{Science} \textbf{357}(6352):661--667. % doi: 10.1126/science.aam8940.
% Islam S, Zeisel A, Joost S, La Manno G, Zajac P, Kasper M, L\"onnerberg P, Linnarsson S. 2014. Quantitative single-cell RNA-seq with unique molecular identifiers. \textit{Nat Methods} \textbf{11}(2):163--166.
% Picelli S, Bj\"orklund \AA K, Faridani OR, Sagasser S, Winberg G, Sandberg R. 2013. Smart-seq2 for sensitive full-length transcriptome profiling in single cells. \textit{Nat Methods} \textbf{10}(11):1096-1098.
% Picelli S, Faridani OR, Bj\"orklund AK, Winberg G, Sagasser S, Sandberg R. 2014. Full-length RNA-seq from single cells using Smart-seq2. \textit{Nat Protoc} \textbf{9}(1):171-181.



\bibitem{Mortazavi2008}Mortazavi A, Williams BA, McCue K, et al. (2008). Mapping and quantifying mammalian transcriptomes by RNA-Seq. \textit{Nat Methods} \textbf{5}(7):621--628

\bibitem{Nagalakshmi2008}Nagalakshmi U, Wang Z, Waern K, et al. (2008). The transcriptional landscape of the yeast genome defined by RNA sequencing. \textit{Science} \textbf{320}(5881):1344--1349. % doi: 10.1126/science.1158441. 

\bibitem{Sultan2008}Sultan M, Schulz MH, Richard H, et al. (2008). A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome. \textit{Science} \textbf{321}(5891):956--960.

\bibitem{Wilhelm2008}Wilhelm BT, Marguerat S, Watt S, et al. (2008). Dynamic repertoire of a eukaryotic transcriptome surveyed at single-nucleotide resolution. \textit{Nature} \textbf{453}(7199):1239--1243.

\bibitem{Tang2009}Tang F, Barbacioru C, Wang Y, et al. (2009). mRNA-Seq whole-transcriptome analysis of a single cell. \textit{Nat Methods} \textbf{6}(5):377--382.

\bibitem{Islam2011}Islam S, Kj\"allquist U, Moliner A, et al. (2011). Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq. \textit{Genome Res} \textbf{21}(7):1160--1167.

\bibitem{Ramdskold2012}Ramsk\"old D, Luo S, Wang YC, et al. (2012). Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells. \textit{Nat Biotechnol} \textbf{30}(8):777--782

\bibitem{Hashimshony2012}Hashimshony T, Wagner F, Sher N, Yanai I. (2012). CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification. \textit{Cell Rep} \textbf{2}(3):666-673. 

\bibitem{Shalek2013}Shalek AK, Satija R, Adiconis X, Gertner RS, Gaublomme JT, Raychowdhury R, Schwartz S, Yosef N, Malboeuf C, Lu D, Trombetta JJ, Gennert D, Gnirke A, Goren A, Hacohen N, Levin JZ, Park H, Regev A. 2013. Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells. \textit{Nature} \textbf{498}(7453):236--240. 

\bibitem{Jaitin2014}Jaitin DA, Kenigsberg E, Keren-Shaul H, Elefant 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. \textit{Science} \textbf{343}(6172):776--779. % doi: 10.1126/science.1247651. % MARS-seq

\bibitem{Klein2015}Klein AM, Mazutis L, Akartuna I, Tallapragada N, Veres A, Li V, Peshkin L, Weitz DA, Kirschner MW. 2015. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. \textit{Cell} \textbf{161}(5):1187--1201. % doi: 10.1016/j.cell.2015.04.044. % InDrop

\bibitem{Macosko2015}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 Individual Cells Using Nanoliter Droplets. \textit{Cell} \textbf{161}(5):1202--1214. % doi: 10.1016/j.cell.2015.05.002. % Drop-seq

\bibitem{10xRNA}Zheng GX, Terry JM, Belgrader P, et al. (2017). Massively parallel digital transcriptional profiling of single cells. \textit{Nat Commun} \textbf{8}:14049. % doi: 10.1038/ncomms14049. % 10x

\bibitem{Microwell-Seq}Han X, Wang R, Zhou Y, et al. (2018). Mapping the Mouse Cell Atlas by Microwell-Seq. \textit{Cell} \textbf{172}(5):1091--1107.e17. % doi: 10.1016/j.cell.2018.02.001.

\bibitem{Cao2017}Cao J, Packer JS, Ramani V, et al. (2017) Comprehensive single-cell transcriptional profiling of a multicellular organism. \textit{Science} \textbf{357}, 661--667. 

\bibitem{Rosenberg2018}Rosenberg AB, Roco CM, Muscat RA, et al. (2018) Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding. \textit{Science} \textbf{360}, 176--182. 

\bibitem{McGhe1981}McGhee JD, Wood WI, Dolan M, et al. (1981) A 200 base pair region at the 5$^{\prime}$ end of the chicken adult $\beta$-globin gene is accessible to nuclease digestion. \textit{Cell} \textbf{27}, 45--55.

\bibitem{Keene1981}Keene MA, Corces V, Lowenhaupt K, et al. (1981) DNase I hypersensitive sites in Drosophila chromatin occur at the 5$^{\prime}$ ends of regions of transcription. \textit{Proc Natl Acad Sci U S A} \textbf{78}, 143--146.

\bibitem{Wu1980}Wu C. (1980) The 5$^{\prime}$ ends of \textit{Drosophila} heat shock genes in chromatin are hypersensitive to DNase I. \textit{Nature} \textbf{286}(5776):854--860.

\bibitem{Minnoye2021}Minnoye L, Marinov GK, Krausgruber T, et al. (2021). Chromatin accessibility profiling methods. \textit{Nat Rev Meth Primers} \textbf{1}:10.

\bibitem{Buenrostro2013}Buenrostro JD, Giresi PG, Zaba LC, et al. (2013) Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. \textit{Nat Methods} \textbf{10}, 1213--1218. % doi: 10.1038/nmeth.2688. 

\bibitem{Corces2017}Corces MR, Trevino AE, Hamilton EG, et al. (2017) An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. \textit{Nat Methods} \textbf{14}, 959--962. % doi: 10.1038/nmeth.4396. 

\bibitem{Reznikoff2008}Reznikoff WS. (2008). Transposon Tn5. \textit{Annu Rev Genet} \textbf{42}:269-86

\bibitem{Adey2010}Adey A, Morrison HG, Asan, et al. (2010) Rapid, low-input, low-bias construction of shotgun fragment libraries by high-density in vitro transposition. \textit{Genome Biol} \textbf{11}(12):R119

\bibitem{Buenrostro2015}Buenrostro JD, Wu B, Litzenburger UM, et al. (2015) Single-cell chromatin accessibility reveals principles of regulatory variation. \textit{Nature} \textbf{523}, 486--490. % doi: 10.1038/nature14590. Epub 2015 Jun 17.

\bibitem{Cusanovich2015}Cusanovich DA, Daza R, Adey A, et al. (2015) Multiplex single cell profiling of chromatin accessibility by combinatorial cellular indexing. \textit{Science} \textbf{348}, 910--914. % doi: 10.1126/science.aab1601. Epub 2015 May 7.

\bibitem{Cusanovich2018}Cusanovich DA, Reddington JP, Garfield DA, et al. (2018) The \textit{cis}-regulatory dynamics of embryonic development at single-cell resolution. \textit{Nature} \textbf{555}, 538--542. % doi: 10.1038/nature25981. 

\bibitem{Preissl2018}Preissl S, Fang R, Huang H, et al. (2018). Single-nucleus analysis of accessible chromatin in developing mouse forebrain reveals cell-type-specific transcriptional regulation. \textit{Nat Neurosci} \textbf{21}(3):432--439.

\bibitem{Mezger2018}Mezger A, Klemm S, Mann I, et al. (2018). High-throughput chromatin accessibility profiling at single-cell resolution. \textit{Nat Commun} \textbf{9}(1):3647. % $\mu$ATAC-seq

\bibitem{10xATAC}Satpathy AT, Granja JM, Yost KE, et al. (2019) Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion.. \textit{Nat Biotechnol} \textbf{37}, 925--936.

\bibitem{Lareau2019}Lareau CA, Duarte FM, Chew JG, et al. (2019) Droplet-based combinatorial indexing for massive-scale single-cell chromatin accessibility. \textit{Nat Biotechnol} \textbf{37}, 916--924.  % dsciATAC-seq

\bibitem{G&T-seq}Macaulay IC, Haerty W, Kumar P, et al. 2015. G\&T-seq: parallel sequencing of single-cell genomes and transcriptomes. \textit{Nat Methods} \textbf{12}(6):519--522. 

\bibitem{PRDD-seq}Huang AY, Li P, Rodin RE, et al. (2020). Parallel RNA and DNA analysis after deep sequencing (PRDD-seq) reveals cell type-specific lineage patterns in human brain. \textit{Proc Natl Acad Sci U S A} \textbf{117}(25):13886--13895.

\bibitem{DNTR-seq}Zachariadis V, Cheng H, Andrews N, Enge M. (2020). A Highly Scalable Method for Joint Whole-Genome Sequencing and Gene-Expression Profiling of Single Cells. \textit{Mol Cell} \textbf{80}(3):541--553.e5. % DNTR-seq

\bibitem{Yin2019}Yin Y, Jiang Y, Lam KG, et al. (2019). High-Throughput Single-Cell Sequencing with Linear Amplification. \textit{Mol Cell} \textbf{76}(4):676-690.e10. % sci-L3-RNA/DNA

\bibitem{TARGET-seq}Rodriguez-Meira A, Buck G, Clark SA, et al. (2019). Unravelling Intratumoral Heterogeneity through High-Sensitivity Single-Cell Mutational Analysis and Parallel RNA Sequencing. \textit{Mol Cell} \textbf{73}(6):1292--1305.e8 % TARGET-seq

\bibitem{scTrio-seq}Hou Y, Guo H, Cao C, et al. (2016). Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas. \textit{Cell Res} \textbf{26}(3):304--319. % doi: 10.1038/cr.2016.23. % scTrio-seq

\bibitem{scMT-seq}Hu Y, Huang K, An Q, Du G, Hu G, Xue J, Zhu X, Wang CY, Xue Z, Fan G. 2016. Simultaneous profiling of transcriptome and DNA methylome from a single cell. \textit{Genome Biol} \textbf{17}:88 % scMT-seq

\bibitem{scM&T-seq}Angermueller C, Clark SJ, Lee HJ, et al. (2016). Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity. \textit{Nat Methods} \textbf{13}(3):229-232. % scM\&T-seq

\bibitem{scNOMe-seq}Pott S. (2017). Simultaneous measurement of chromatin accessibility, DNA methylation, and nucleosome phasing in single cells. \textit{Elife} \textbf{6}:e23203. % scNOMe-seq

\bibitem{REAP-seq}Peterson VM, Zhang KX, Kumar N, et al. (2017). Multiplexed quantification of proteins and transcripts in single cells. \textit{Nat Biotechnol} \textbf{35}(10):936--939. % doi: 10.1038/nbt.3973. % REAP-seq

\bibitem{CITE-seq}Stoeckius M, Hafemeister C, Stephenson W, et al. (2017). Simultaneous epitope and transcriptome measurement in single cells. \textit{Nat Methods} \textbf{14}(9):865--868. % doi: 10.1038/nmeth.4380. % CITE-seq

\bibitem{QBC}O'Huallachain M, Bava FA, et al. (2020). Ultra-high throughput single-cell analysis of proteins and RNAs by split-pool synthesis. \textit{Commun Biol} \textbf{3}(1):213 % QBC

\bibitem{inCITE-seq}Chung H, Parkhurst CN, Magee EM, et al. (2021). Simultaneous single cell measurements of intranuclear proteins and gene expression

\bibitem{iNS-seq}Katzenelenbogen Y, Sheban F, Yalin A, et al. (2020). Coupled scRNA-Seq and Intracellular Protein Activity Reveal an Immunosuppressive Role of TREM2 in Cancer. \textit{Cell} \textbf{182}(4):872--885.e19 % iNS-seq

\bibitem{Guo2017}Guo F, Li L, Li J, et al. (2017). Single-cell multi-omics sequencing of mouse early embryos and embryonic stem cells. \textit{Cell Res} \textbf{27}(8):967--988. % doi: 10.1038/cr.2017.82. Epub 2017 Jun 16. % COOL-seq

\bibitem{scNMT-seq}Clark SJ, Argelaguet R, Kapourani CA, et al. (2018). scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells. \textit{Nat Commun} \textbf{9}(1):781. % doi: 10.1038/s41467-018-03149-4.

\bibitem{scNOMeRe-seq}Wang Y, Yuan P, Yan Z, et al. (2021). Single-cell multiomics sequencing reveals the functional regulatory landscape of early embryos. \textit{Nat Commun} \textbf{12}(1):1247. % scNOMeRe-seq

\bibitem{snmC2T-seq}Luo C, Liu H, Xie F, et al. (2019) Single nucleus multi-omics links human cortical cell regulatory genome diversity to disease risk variants. \textit{bioRxiv} 2019.12.11.873398.

\bibitem{CoTECH}Xiong H, Luo Y, Wang Q, et al. (2021). Single-cell joint detection of chromatin occupancy and transcriptome enables higher-dimensional epigenomic reconstructions. \textit{Nat Methods} \textbf{18}(6):652--660. % CoTECH

\bibitem{Paired-Tag}Zhu C, Zhang Y, Li YE, et al. (2021). Joint profiling of histone modifications and transcriptome in single cells from mouse brain. \textit{Nat Methods} \textbf{18}(3):283--292. % Paired-Tag

\bibitem{scDamT-seq}Markodimitraki CM, Rang FJ, Rooijers K, et al. (2020). Simultaneous quantification of protein-DNA interactions and transcriptomes in single cells with scDam\&T-seq. \textit{Nat Protoc} \textbf{15}(6):1922--1953.

\bibitem{PHAGE-ATAC}Fiskin E, Lareau CA, Eraslan G, et al. (2020). Single-cell multimodal profiling of proteins and chromatin accessibility using PHAGE-ATAC. \textit{bioRxiv} 2020.10.01.322420

\bibitem{Mimitou2021}Mimitou EP, Lareau CA, Chen KY, et al. (2021). Scalable, multimodal profiling of chromatin accessibility, gene expression and protein levels in single cells. \textit{Nat Biotechnol} doi: 10.1038/s41587-021-00927-2

\bibitem{Swanson2021}Swanson E, Lord C, Reading J, et al. (2021). Simultaneous trimodal single-cell measurement of transcripts, epitopes, and chromatin accessibility using TEA-seq. \textit{Elife} \textbf{10}:e63632

\bibitem{SUGAR-seq}Kearney CJ, Vervoort SJ, Ramsbottom KM, et al. (2021). SUGAR-seq enables simultaneous detection of glycans, epitopes, and the transcriptome in single cells. \textit{Sci Adv} \textbf{7}(8):eabe3610.

\bibitem{Cao2018}Cao J, Cusanovich DA, Ramani V, et al. (2018) Joint profiling of chromatin accessibility and gene expression in thousands of single cells. \textit{Science} 361, 1380--1385. % doi: 10.1126/science.aau0730. 

\bibitem{Zhu2019}Zhu C, Yu M, Huang H, et al. (2019) An ultra high-throughput method for single-cell joint analysis of open chromatin and transcriptome. \textit{Nat Struct Mol Biol} \textbf{26}, 1063--1070. % Paired-seq

\bibitem{ASTAR-seq}Xing QR, Farran CAE, Zeng YY, et al. (2020). Parallel bimodal single-cell sequencing of transcriptome and chromatin accessibility. \textit{Genome Res} \textbf{30}(7):1027--1039. % ASTAR-seq

\bibitem{SNARE-seq}Chen S, Lake BB, Zhang K. (2019). High-throughput sequencing of the transcriptome and chromatin accessibility in the same cell. \textit{Nat Biotechnol} \textbf{37}(12):1452--1457. % SNARE-seq

\bibitem{Ma2020}Ma S, Zhang B, LaFave LM, et al. (2020) Chromatin Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin. \textit{Cell} \textbf{183}, 1103--1116.e20

\bibitem{Langmead2009}Langmead B, Trapnell C, Pop M, et al. (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. \textit{Genome Biol} \textbf{10}, R25.

\bibitem{Li2009a}Li H, Handsaker B, Wysoker A, et al. (2009) The Sequence Alignment/Map format and SAMtools. \textit{Bioinformatics} \textbf{25}, 2078--2079.

\bibitem{Kuhn2013}Kuhn RM, Haussler D, Kent WJ (2013) The UCSC genome browser and associated tools. \textit{Brief Bioinform} \textbf{14}, 144--161.

\bibitem{Kent2010}Kent WJ, Zweig AS, Barber G, et al. (2010) BigWig and BigBed: enabling browsing of large distributed datasets. \textit{Bioinformatics} \textbf{26}, 2204--2207.

\bibitem{STAR}Dobin A, Davis CA, Schlesinger F, et al. (2013). STAR: ultrafast universal RNA-seq aligner. \textit{Bioinformatics} \textbf{29}(1):15--21.

\bibitem{ArchR}Granja JM, Corces MR, Pierce SE, et al. (2021). ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis. \textit{Nat Genet} \textbf{53}(3):403--411.

\bibitem{Seurat}Hao Y, Hao S, Andersen-Nissen E, et al. (2021). Integrated analysis of multimodal single-cell data. \textit{Cell} \textbf{184}(13):3573--3587.e29.

\bibitem{ENCODE2012}ENCODE Project Consortium. (2012) An integrated encyclopedia of DNA elements in the human genome. \textit{Nature} \textbf{489}, 57--74.

\bibitem{Marinov2014}Marinov GK, Wang YE, Chan DC, Wold BJ. (2014). Evidence for site-specific occupancy of the mitochondrial genome by nuclear transcription factors. \textit{PLoS ONE} \textbf{9}(1):e84713. (\href{https://www.ncbi.nlm.nih.gov/pubmed/24465428}{link})

\bibitem{Picelli2014}Picelli S, Bj\"orklund AK, Reinius B, et al. (2014) Tn5 transposase and tagmentation procedures for massively scaled sequencing projects. \textit{Genome Res} \textbf{24}, 2033--2040. % doi: 10.1101/gr.177881.114. Epub 2014 Jul 30.

\bibitem{Domcke2020}Domcke S, Hill AJ, Daza RM, et al. (2020). A human cell atlas of fetal chromatin accessibility. \textit{Science} \textbf{370}(6518):eaba7612

\bibitem{Corces2018}Corces MR, Granja JM, Shams S, et al. (2018). The chromatin accessibility landscape of primary human cancers. \textit{Science} \textbf{362}(6413):eaav1898