Cell fixation and preservation for droplet-based single-cell transcriptomics
Open accessPublished version of a preprint
Abstract
BACKGROUND: Recent developments in droplet-based microfluidics allow the transcriptional profiling of thousands of individual cells in a quantitative, highly parallel and cost-effective way. A critical, often limiting step is the preparation of cells in an unperturbed state, not altered by stress or ageing. Other challenges are rare cells that need to be collected over several days or samples prepared at different times or locations. METHODS: Here, we used chemical fixation to address these problems. Methanol fixation allowed us to stabilise and preserve dissociated cells for weeks without compromising single-cell RNA sequencing data. RESULTS: By using mixtures of fixed, cultured human and mouse cells, we first showed that individual transcriptomes could be confidently assigned to one of the two species. Single-cell gene expression from live and fixed samples correlated well with bulk mRNA-seq data. We then applied methanol fixation to transcriptionally profile primary cells from dissociated, complex tissues. Low RNA content cells from Drosophila embryos, as well as mouse hindbrain and cerebellum cells prepared by fluorescence-activated cell sorting, were successfully analysed after fixation, storage and single-cell droplet RNA-seq. We were able to identify diverse cell populations, including neuronal subtypes. As an additional resource, we provide 'dropbead', an R package for exploratory data analysis, visualization and filtering of Drop-seq data. CONCLUSIONS: We expect that the availability of a simple cell fixation method will open up many new opportunities in diverse biological contexts to analyse transcriptional dynamics at single-cell resolution.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
scRNA-seq methods require fresh tissues, which can be difficult to obtain and lead to logistic complexities.
“First, these methods require the use of fresh tissues, which can be difficult to obtain and thus lead to logistic complexities (Alles et al., 2017; Attar et al., 2018; Wang et al., 2018; Lafzi et al., 2018).”
From Robust single-nucleus RNA sequencing reveals depot-specific cell population dynamics in adipose tissue remodeling during obesity (2025) · cites this paper as Alles et al., 2017
The Background and Conclusions (pages not provided) describe difficulties preparing unperturbed cells, collecting rare cells, transporting clinical specimens, and coordinating experiments. But the paper demonstrates that fixed cells can be stored and used for droplet-based scRNA-seq, so it does not support the categorical claim that these methods require fresh tissues. (LLM, conf=0.88)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709 · cited 2× · see citing works
“The reads were then aligned to a combined FASTA file of the hg38 and mm10 reference genomes, using STAR (13) v. 2.4.0j with default parameters.”
MethodInfluentialMassively parallel digital transcriptional profiling of single cells
Zheng, G. X. Y., Terry, J. M., Belgrader, P., Ryvkin, P., Bent, Z. W., Wilson, R., Ziraldo, S. B., Wheeler, T. D., McDermott, G. P., Zhu, J., et al. (2017) · Nature Communications · doi:10.1038/ncomms14049 · Cited by 7,353 · cited 3× · see citing works
“tain more RNA than oftentimes smaller, primary cells [18], Drop-seq can be successfully performed with fixed”
InfluentialHighly parallel genome-wide expression profiling of individual cells using nanoliter droplets.
Macosko, E. Z., Basu, A., Satija, R., Nemesh, J., Shekhar, K., Goldman, M., Tirosh, I., Bialas, A. R., Kamitaki, N., Martersteck, E. M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.05.002 · Cited by 7,110 · cited 10× · see citing works
“Preparation kit (Illumina, San Diego, CA, USA) using custom primers that amplified only the 3' ends [7].”
BackgroundMethodInfluentialSpatial reconstruction of single-cell gene expression data
Satija, R., Farrell, J. A., Gennert, D., Schier, A. F., & Regev, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3192 · Cited by 7,055 · cited 2× · see citing works
“For the Drosophila embryos and mouse hindbrain samples, after filtering our samples with ‘dropbead’ we used Seurat [17] for cluster analysis.”
BackgroundMethodmRNA-Seq whole-transcriptome analysis of a single cell
Tang, F., Barbacioru, C., Wang, Y., Nordman, E., Lee, C., Xu, N., Wang, X., Bodeau, J., Tuch, B. B., Siddiqui, A., et al. (2009) · Nature Methods · doi:10.1038/nmeth.1315 · Cited by 3,969 · cited 1× · see citing works
“Rather than studying global gene expression of a tissue as a whole, it has been recognized that transcriptional profiling at a single-cell resolution (1-4) provides a much more complete and accurate description of its biological function (5,6).”
BackgroundDroplet barcoding for single-cell transcriptomics applied to embryonic stem cells
Klein, A. M., Mazutis, L., Akartuna, I., Tallapragada, N., Veres, A., Li, V., Peshkin, L., Weitz, D. A., & Kirschner, M. W. (2015) · Cell · doi:10.1016/j.cell.2015.04.044 · Cited by 3,356 · cited 2× · see citing works
“It also remains to be determined whether methanol fixation is compatible with the ‘InDrop’ protocol [8], another, recently developed droplet-based sequencing approach that involves a different detergent for cell lysis and cDNA library construction.”
BackgroundSmart-seq2 for sensitive full-length transcriptome profiling in single cells
Picelli, S., Björklund, Å. K., Faridani, O. R., Sagasser, S., Winberg, G., & Sandberg, R. (2013) · Nature Methods · doi:10.1038/nmeth.2639 · Cited by 2,358 · cited 1× · see citing works
“Rather than studying global gene expression of a tissue as a whole, it has been recognized that transcriptional profiling at a single-cell resolution (1-4) provides a much more complete and accurate description of its biological function (5,6).”
BackgroundMassively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types
Jaitin, D. A., Kenigsberg, E., Keren-Shaul, H., Elefant, N., Paul, F., Zaretsky, I., Mildner, A., Cohen, N., Jung, S., Tanay, A., et al. (2014) · Science · doi:10.1126/science.1247651 · Cited by 1,795 · see citing works
Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding
Rosenberg, A. B., Roco, C. M., Muscat, R. A., Kuchina, A., Sample, P., Yao, Z., Graybuck, L. T., Peeler, D. J., Mukherjee, S., Chen, W., et al. (2018) · Science · doi:10.1126/science.aam8999 · Cited by 1,422 · see citing works
Cao, J., Packer, J. S., Ramani, V., Cusanovich, D. A., Huynh, C., Daza, R., Qiu, X., Lee, C., Furlan, S. N., Steemers, F. J., et al. (2017) · doi:10.1101/104844 · Cited by 1,402 · see citing works
Single-cell genome sequencing: current state of the science
Gawad, C., Koh, W., & Quake, S. R. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2015.16 · Cited by 1,334 · cited 1× · see citing works
“Rather than studying global gene expression of a tissue as a whole, it has been recognized that transcriptional profiling at a single-cell resolution [1–4] provides a much more complete and accurate description of its biological function [5, 6].”
BackgroundEffect of Fixatives and Tissue Processing on the Content and Integrity of Nucleic Acids
Srinivasan, M., Sedmak, D. D., & Jewell, S. D. (2002) · American Journal Of Pathology · doi:10.1016/s0002-9440(10)64472-0 · Cited by 1,320 · cited 2× · see citing works
“Cross-linking induces chemical modifications that inhibit poly(dT) annealing, reverse transcriptase and cDNA synthesis, making cross-link reversal necessary [10].”
Oligodendrocyte heterogeneity in the mouse juvenile and adult central nervous system
Marques, S., Zeisel, A., Codeluppi, S., van Bruggen, D., Mendanha Falcão, A., Xiao, L., Li, H., Häring, M., Hochgerner, H., Romanov, R. A., et al. (2016) · Science · doi:10.1126/science.aaf6463 · Cited by 1,246 · see citing works
CEL-seq: single-cell RNA-seq by multiplexed linear amplification
Hashimshony, T., Wagner, F., Sher, N., & Yanai, I. (2012) · Cell Reports · doi:10.1016/j.celrep.2012.08.003 · Cited by 1,231 · cited 1× · see citing works
“Rather than studying global gene expression of a tissue as a whole, it has been recognized that transcriptional profiling at a single-cell resolution (1-4) provides a much more complete and accurate description of its biological function (5,6).”
BackgroundSingle-cell RNA-seq: advances and future challenges
Saliba, A.-E., Westermann, A. J., Gorski, S. A., & Vogel, J. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku555 · Cited by 847 · cited 1× · see citing works
“handling of cellular input material [9].”
Classification of low quality cells from single-cell RNA-seq data
Ilicic, T., Kim, J. K., Kolodziejczyk, A. A., Bagger, F. O., McCarthy, D. J., Marioni, J. C., & Teichmann, S. A. (2016) · Genome Biology · doi:10.1186/s13059-016-0888-1 · Cited by 693 · cited 3× · see citing works
“Stressed or broken cells lose non-mitochondrially encoded, cytoplasmically localized mRNAs [16].”
BackgroundMethodInfluentialGlobal analysis of patterns of gene expression during Drosophilaembryogenesis
Tomančák, P., Berman, B. P., Beaton, A., Weiszmann, R., Kwan, E., Hartenstein, V., Celniker, S., & Rubin, G. M. (2007) · Genome biology · doi:10.1186/gb-2007-8-7-r145 · Cited by 453 · cited 1× · see citing works
“Tissues were assigned through imaging gene ontology (ImaGO) term analysis [20] of the 50 most variable genes in each cluster (Additional file 5: Table S1) as a first approximation, followed by inspection of publicly available RNA in situ staining patterns [21] of highly variable as well as other known tissue-specific…”
MethodSingle Cell Genomics: Advances and Future Perspectives
Macaulay, I. C., & Voet, T. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004126 · Cited by 384 · cited 1× · see citing works
“Rather than studying global gene expression of a tissue as a whole, it has been recognized that transcriptional profiling at a single-cell resolution [1–4] provides a much more complete and accurate description of its biological function [5, 6].”
BackgroundFlyMine: an integrated database for Drosophila and Anopheles genomics
Lyne, R., Smith, R. N., Rutherford, K., Wakeling, M. N., Varley, A., Guillier, F., Janssens, H., Ji, W., Mclaren, P., North, P., et al. (2007) · Genome biology · doi:10.1186/gb-2007-8-7-r129 · Cited by 376 · cited 2× · see citing works
“associations were made by ImaGO term analysis [20] on the 50 most variable genes of each cluster (Additional file 5: Table S1), followed by inspection”
MethodThe Drosophila embryo at single-cell transcriptome resolution
Karaiskos, N., Wahle, P., Alles, J., Boltengagen, A., Ayoub, S., Kipar, C., Kocks, C., Rajewsky, N., & Zinzen, R. P. (2017) · Science · doi:10.1126/science.aan3235 · Cited by 371 · cited 2× · see citing works
“We also found that single-cell sequencing data from methanol-fixed cells were of sufficient quality to carry out spatial mapping and 3D reconstruction of a virtual Drosophila embryo at the onset of gastrulation [14].”
BackgroundSelf-citationFixed single-cell transcriptomic characterization of human radial glial diversity
Thomsen, E. R., Mich, J. K., Yao, Z., Hodge, R. D., Doyle, A. M., Jang, S., Shehata, S. I., Nelson, A. M., Shapovalova, N. V., Levi, B. P., et al. (2015) · Nature Methods · doi:10.1038/nmeth.3629 · Cited by 227 · cited 1× · see citing works
“Another study describes fixation of cells by cross-linking with formaldehyde [25], followed by reverse cross-linking (breakage of methylene bridges between protein and RNA molecules with heat).”
BackgroundSingle-cell transcriptome conservation in cryopreserved cells and tissues
Guillaumet-Adkins, A., Rodríguez-Esteban, G., Mereu, E., Méndez-Lago, M., Jaitin, D. A., Villanueva, A., Vidal, A., Martínez‐Martí, A., Felip, E., Vivancos, A. P., et al. (2017) · Genome biology · doi:10.1186/s13059-017-1171-9 · Cited by 158 · cited 1× · see citing works
“One study uses cryopreservation followed by flow cytometry to sort single cells for subsequent processing [24].”
Large-scale sorting of C. elegans embryos reveals the dynamics of small RNA expression
Stoeckius, M., Maaskola, J., Colombo, T., Rahn, H.-P., Friedländer, M. R., Li, N., Chen, W., Piano, F., & Rajewsky, N. (2009) · Nature Methods · doi:10.1038/nmeth.1370 · Cited by 92 · cited 10× · see citing works
“Mitochondrially encoded transcripts are not elevated in methanol-fixed cells An increase in the proportion of transcripts from mitochondrial genes (37 mtDNA-encoded mRNAs) is believed to indicate low quality cells that are broken or damaged to varying degrees (14).”
BackgroundMethodInfluentialSelf-citationCherbas, L., & Gong, L. (2014) · Methods · doi:10.1016/j.ymeth.2014.01.006 · Cited by 40 · see citing works
Esser, C., Göttlinger, C., Kremer, J., Hundeiker, C., & Radbruch, A. (1995) · Cytometry · doi:10.1002/cyto.990210411 · Cited by 39 · see citing works
Scaling single cell transcriptomics through split pool barcodingPreprint
Rosenberg, A. B., Roco, C. M., Muscat, R. A., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/105163 · Cited by 39 · see citing works
GXD: a community resource of mouse Gene Expression Data
Smith, C. M., Finger, J. H., Hayamizu, T. F., McCright, I. J., Xu, J., Eppig, J. T., Kadin, J. A., Richardson, J. E., & Ringwald, M. (2015) · Mammalian Genome · doi:10.1007/s00335-015-9563-1 · Cited by 23 · cited 1× · see citing works
“Markers were confirmed to be expressed in newborn hindbrain and cerebellum by inspecting RNA in situ hybridization images in publicly available databases [22, 23].”
Background
Flagged first, then by citations
Cited by
Sorted by citations
A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications
Haque, A., Engel, J., Teichmann, S. A., & Lönnberg, T. (2017) · Genome Medicine · doi:10.1186/s13073-017-0467-4 · Cited by 1,071 · see citing works
“Furthermore, over the past few years, protocols compatible with certain cell-fixation methods have started to emerge [34, 35, 38, 54, 55].”
BackgroundMultiplexed quantification of proteins and transcripts in single cells
Peterson, V. M., Zhang, K. X., Kumar, N., Wong, J., Li, L., Wilson, D. C., Moore, R., McClanahan, T. K., Sadekova, S., & Klappenbach, J. A. (2017) · Nature Biotechnology · doi:10.1038/nbt.3973 · Cited by 832 · see citing works
Wu, H., Kirita, Y., Donnelly, E. L., & Humphreys, B. D. (2019) · Journal of the American Society of Nephrology · doi:10.1681/asn.2018090912 · Cited by 752 · see citing works
Dissecting cell identity via network inference and in silico gene perturbation
Kamimoto, K., Stringa, B., Hoffmann, C. M., Jindal, K., Solnica-Krezel, L., & Morris, S. A. (2023) · Nature · doi:10.1038/s41586-022-05688-9 · Cited by 677 · see citing works
Denisenko, E., Guo, B. B., Jones, M., Hou, R., de Kock, L., Lassmann, T., Poppe, D., Clément, O., Simmons, R. K., Lister, R., et al. (2020) · Genome Biology · doi:10.1186/s13059-020-02048-6 · Cited by 686 · see citing works
“Some of the artifacts have been investigated in recent studies comparing single-cell profiles of methanol-fixed and live cells [21, 22], cryopreserved and live cells [22, 23], single-cell and single-nucleus protocols [24–26], or tissue dissociation using cold-active protease and traditional digestion at 37 °C [18].”
BackgroundMadissoon, E., Wilbrey-Clark, A., Miragaia, R. J., Saeb‐Parsy, K., Mahbubani, K. T. A., Georgakopoulos, N., Harding, P., Polański, K., Huang, N., Nowicki-Osuch, K., et al. (2019) · Genome biology · doi:10.1186/s13059-019-1906-x · Cited by 492 · see citing works
Katzenelenbogen, Y., Sheban, F., Yalin, A., Yofe, I., Svetlichnyy, D., Jaitin, D. A., Bornstein, C., Moshe, A., Keren-Shaul, H., Cohen, M., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.032 · Cited by 498 · see citing works
Cell type atlas and lineage tree of a whole complex animal by single-cell transcriptomics
Plass, M., Solana, J., Wolf, F. A., Ayoub, S., Misios, A., Glažar, P., Obermayer, B., Theis, F. J., Kocks, C., & Rajewsky, N. (2018) · Science · doi:10.1126/science.aaq1723 · Cited by 474 · see citing works
“Eight of 11 samples were fixed with methanol (28) or frozen with dimethyl sulfoxide (DMSO) (29) to facilitate sample handling.”
MethodSelf-citationSingle-cell mapping of lineage and identity in direct reprogramming
Biddy, B. A., Kong, W., Kamimoto, K., Guo, C., Waye, S. E., Sun, T., & Morris, S. A. (2018) · Nature · doi:10.1038/s41586-018-0744-4 · Cited by 382 · see citing works
The Drosophila embryo at single-cell transcriptome resolution
Karaiskos, N., Wahle, P., Alles, J., Boltengagen, A., Ayoub, S., Kipar, C., Kocks, C., Rajewsky, N., & Zinzen, R. P. (2017) · Science · doi:10.1126/science.aan3235 · Cited by 371 · see citing works
“approach to avoid heterogeneity is cell culture (5-11), but the amount of genomic and transcriptomic variation within most cell lines has been shown to be substantial and cultured cells are often poor in vivo proxies.”
BackgroundSelf-citationUnravelling biology and shifting paradigms in cancer with single-cell sequencing
Baslan, T., & Hicks, J. B. (2017) · Nature reviews. Cancer · doi:10.1038/nrc.2017.58 · Cited by 377 · see citing works
Stephenson, W., Donlin, L. T., Butler, A., Rozo, C. T., Bracken, B., Rashidfarrokhi, A., Goodman, S. M., Ivashkiv, L. B., Bykerk, V. P., Orange, D. E., et al. (2018) · Nature Communications · doi:10.1038/s41467-017-02659-x · Cited by 365 · see citing works
Spatiotemporal single-cell analysis of gene expression in the mouse suprachiasmatic nucleus
Wen, S., Ma, D., Zhao, M., Xie, L., Wu, Q., Gou, L., Zhu, C., Fan, Y., Wang, H., & Yan, J. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0586-x · Cited by 328 · see citing works
Genetic mapping of cell type specificity for complex traits
Watanabe, K., Mirkov, M. U., de Leeuw, C., van den Heuvel, M. P., & Posthuma, D. (2019) · Nature Communications · doi:10.1038/s41467-019-11181-1 · Cited by 323 · see citing works
Richards, L. M., Whitley, O., MacLeod, G. D. A. H., Cavalli, F. M. G., Coutinho, F. J., Jaramillo, J. E., Svergun, N., Riverin, M., Croucher, D. C., Kushida, M. M., et al. (2021) · Nature Cancer · doi:10.1038/s43018-020-00154-9 · Cited by 304 · see citing works
scds: computational annotation of doublets in single-cell RNA sequencing data
Bais, A. S., & Kostka, D. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btz698 · Cited by 308 · see citing works
Identification of a Master Regulator of Differentiation in Toxoplasma
Waldman, B. S., Schwarz, D., Wadsworth, M. H., Saeij, J. P. J., Shalek, A. K., & Lourido, S. (2020) · Cell · doi:10.1016/j.cell.2019.12.013 · Cited by 266 · see citing works
H3K9me3-heterochromatin loss at protein-coding genes enables developmental lineage specification
Nicetto, D., Donahue, G., Jain, T., Peng, T., Sidoli, S., Sheng, L., Montavon, T., Becker, J. S., Grindheim, J. M., Blahnik, K. R., et al. (2019) · Science · doi:10.1126/science.aau0583 · Cited by 241 · see citing works
Single-nucleus and in situ RNA-sequencing reveal cell topographies in the human pancreas
Tosti, L., Hang, Y., Debnath, O., Tiesmeyer, S., Trefzer, T., Steiger, K., Ten, F. W., Lukassen, S., Ballke, S., Kühl, A. A., et al. (2021) · Gastroenterology · doi:10.1053/j.gastro.2020.11.010 · Cited by 228 · see citing works
“, 2018), methanol fixation (Alles et al., 2017; Chen et al., 2018), or the addition of RNAse inhibitors like ribonucleoside vanadyl complexes (Shieh et al.”
BackgroundTutorial: guidelines for the experimental design of single-cell RNA sequencing studies
Lafzi, A., Moutinho, C., Picelli, S., & Heyn, H. (2018) · Nature Protocols · doi:10.1038/s41596-018-0073-y · Cited by 218 · see citing works
“Similarly, methanol fixation has been established as an alternative for droplet-based single-cell methods, which could also avoid technically induced variations in gene expression triggered by prolonged sample processing time 23 .”
BackgroundKim, M., Franke, V., Brandt, B., Lowenstein, E. D., Schoewel, V., Spuler, S., Akalin, A., & Birchmeier, C. (2020) · Nature Communications · doi:10.1038/s41467-020-20064-9 · Cited by 207 · see citing works
Self-citationTumor Functional Heterogeneity Unraveled by scRNA-seq Technologies
González-Silva, L., Quevedo, L., & Varela, I. (2020) · Trends in cancer · doi:10.1016/j.trecan.2019.11.010 · Cited by 200 · see citing works
The Myeloid Cell Compartment—Cell by Cell
Bassler, K. E., Schulte-Schrepping, J., Warnat‐Herresthal, S., Aschenbrenner, A. C., & Schultze, J. L. (2019) · Annual Review of Immunology · doi:10.1146/annurev-immunol-042718-041728 · Cited by 191 · see citing works
Zywitza, V., Misios, A., Bunatyan, L., Willnow, T. E., & Rajewsky, N. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.11.003 · Cited by 183 · see citing works
Self-citationExperimental Considerations for Single-Cell RNA Sequencing Approaches
Nguyen, Q. H., Pervolarakis, N., Nee, K., & Kessenbrock, K. (2018) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2018.00108 · Cited by 170 · see citing works
Massively parallel and time-resolved RNA sequencing in single cells with scNT-seq
Qiu, Q., Hu, P., Qiu, X., Govek, K. W., Cámara, P. G., & Wu, H. (2020) · Nature Methods · doi:10.1038/s41592-020-0935-4 · Cited by 172 · see citing works
Independence of chromatin conformation and gene regulation during Drosophila dorsoventral patterning
Ing-Simmons, E., Vaid, R., Bing, X. Y., Levine, M., Mannervik, M., & Vaquerizas, J. M. (2021) · Nature Genetics · doi:10.1038/s41588-021-00799-x · Cited by 159 · see citing works
A Single-Cell Transcriptome Atlas of the Mouse Glomerulus
Karaiskos, N., Rahmatollahi, M., Boltengagen, A., Liu, H., Hoehne, M., Rinschen, M. M., Schermer, B., Benzing, T. R., Rajewsky, N., Kocks, C., et al. (2018) · Journal of the American Society of Nephrology · doi:10.1681/asn.2018030238 · Cited by 166 · see citing works
Self-citationPBMC fixation and processing for Chromium single-cell RNA sequencing
Chen, J., Cheung, F., Shi, R., Zhou, H., Lu, W., Candia, J., Kotliarov, Y., Stagliano, K. R., & Tsang, J. S. (2018) · Journal of Translational Medicine · doi:10.1186/s12967-018-1578-4 · Cited by 157 · see citing works
Inak, G., Rybak‐Wolf, A., Lisowski, P., Pentimalli, T. M., Jüttner, R., Glažar, P., Uppal, K., Bottani, E., Brunetti, D., Secker, C., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-22117-z · Cited by 142 · see citing works
Self-citationExperimental design for single-cell RNA sequencing
Baran‐Gale, J., Chandra, T., & Kirschner, K. (2017) · Briefings in Functional Genomics · doi:10.1093/bfgp/elx035 · Cited by 128 · see citing works
Wyler, E., Franke, V., Menegatti, J., Kocks, C., Boltengagen, A., Praktiknjo, S. D., Walch‐Rückheim, B., Bosse, J. B., Rajewsky, N., Grässer, F. A., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-12894-z · Cited by 130 · see citing works
Self-citationSingle Cell RNA Sequencing of Rare Immune Cell Populations
Nguyen, A., Khoo, W. H., Moran, I., Croucher, P. I., & Phan, T. G. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.01553 · Cited by 120 · see citing works
“Recent advances have found scRNA-Seq can also be performed on cryopreserved (25, 26) or fixed cells (27, 28) and cryopreserved cells were found to have a similar scRNA-Seq transcriptional profile to freshly isolated cells (25).”
BackgroundSpinal macrophages resolve nociceptive hypersensitivity after peripheral injury
Niehaus, J. K., Taylor‐Blake, B., Loo, L., Simon, J. M., & Zylka, M. J. (2021) · Neuron · doi:10.1016/j.neuron.2021.02.018 · Cited by 120 · see citing works
An Introduction to the Analysis of Single-Cell RNA-Sequencing Data
Aljanahi, A. A., Danielsen, M., & Dunbar, C. E. (2018) · Molecular Therapy — Methods & Clinical Development · doi:10.1016/j.omtm.2018.07.003 · Cited by 116 · see citing works
“Another common QC metric is the number of mitochondrial gene transcripts.(32,33,35,39,40) High numbers of mitochondrial transcripts are indicators of cell stress,(41) and therefore cells with elevated mitochondrial gene expression are often not included in the analysis, because most experiments will not benefit from c…”
BackgroundA multicenter study benchmarking single-cell RNA sequencing technologies using reference samples
Chen, W., Zhao, Y., Chen, X., Yang, Z., Xu, X., Bi, Y., Chen, V., Li, J., Choi, H., Ernest, B., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-00748-9 · Cited by 114 · see citing works
Wohnhaas, C. T., Leparc, G. G., Fernandez-Albert, F., Kind, D., Gantner, F., Viollet, C., Hildebrandt, T., & Baum, P. (2019) · Scientific Reports · doi:10.1038/s41598-019-46932-z · Cited by 105 · see citing works
Droplet-based single cell RNAseq tools: a practical guide
Salomon, R., Kaczorowski, D., Valdes-Mora, F., Nordon, R. E., Neild, A., Farbehi, N., Bartonicek, N., & Gallego-Ortega, D. (2019) · Lab on a Chip · doi:10.1039/c8lc01239c · Cited by 109 · see citing works
Inertial-ordering-assisted droplet microfluidics for high-throughput single-cell RNA-sequencing
Moon, H., Je, K., Min, J.-W., Park, D., Han, K., Shin, S., Park, W., Yoo, C. E., & Kim, S. (2018) · Lab on a Chip · doi:10.1039/c7lc01284e · Cited by 105 · see citing works
ACME dissociation: a versatile cell fixation-dissociation method for single-cell transcriptomics
García-Castro, H., Kenny, N. J., Iglesias, M., Álvarez‐Campos, P., Mason, V., Elek, A., Schönauer, A., Sleight, V. A., Neiro, J., Aboobaker, A. A., et al. (2021) · Genome biology · doi:10.1186/s13059-021-02302-5 · Cited by 108 · see citing works
“One disadvantage of enzymatic approaches is that cells can only be cryopreserved after dissociation, typically by FACS sorting them into methanol [52] or DMSO-containing solutions [46].”
BackgroundDesign and application of single-cell RNA sequencing to study kidney immune cells in lupus nephritis
Rao, D. A., Arazi, A., Wofsy, D., & Diamond, B. (2019) · Nature Reviews Nephrology · doi:10.1038/s41581-019-0232-6 · Cited by 96 · see citing works
Kong, W., Biddy, B. A., Kamimoto, K., Amrute, J., Butka, E. G., & Morris, S. A. (2020) · Nature Protocols · doi:10.1038/s41596-019-0247-2 · Cited by 93 · see citing works
“61 Prepare a portion of cells for methanol fixation (adapted from Alles et al.(66)) by transferring a minimum of 10,000 cells into a 1.”
BackgroundInfluentialUnravelling glioblastoma heterogeneity by means of single-cell RNA sequencing
Martínez, A. H., Madurga, R., Garcia‐Romero, N., & Ayuso‐Sacido, Á. (2021) · Cancer Letters · doi:10.1016/j.canlet.2021.12.008 · Cited by 93 · see citing works
Recent Advances in Methods for Circulating Tumor Cell Detection
Vidlařová, M., Řehulková, A., Stejskal, P., Prokopova, A., Slavík, H., Hajdúch, M., & Srovnal, J. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24043902 · Cited by 91 · see citing works
Recent Advances in Droplet-based Microfluidic Technologies for Biochemistry and Molecular Biology
Barea, J. S., Lee, J., & Kang, D. (2019) · Micromachines · doi:10.3390/mi10060412 · Cited by 86 · see citing works
“The cell type composition can be determined by single-nucleus RNA-sequencing which can analyze transcriptional states in vivo and cell fixation methods contribute to a better resolution [126,127].”
BackgroundPiGx: reproducible genomics analysis pipelines with GNU Guix
Wurmus, R., Uyar, B., Osberg, B., Franke, V., Blume, A., Wreczycka, K., Ronen, J., & Akalin, A. (2018) · GigaScience · doi:10.1093/gigascience/giy123 · Cited by 82 · see citing works
“barcodes (Alles et al. 2017), and constructs digital expression matrices for each sample (each saved in loom format); loom files from all samples are then merged into one large loom file using the loompy package (Linnarsson 2018).”
Evolutionary cell type mapping with single-cell genomics
Tanay, A., & Sebé-Pedrós, A. (2021) · Trends in Genetics · doi:10.1016/j.tig.2021.04.008 · Cited by 75 · see citing works
Developmental single-cell transcriptomics in the Lytechinus variegatus sea urchin embryo
Massri, A. J., Greenstreet, L., Afanassiev, A., Berrío, A., Wray, G. A., Schiebinger, G. R., & McClay, D. R. (2021) · Development · doi:10.1242/dev.198614 · Cited by 82 · see citing works
CellOracle: Dissecting cell identity via network inference and in silico gene perturbation
Kamimoto, K., Hoffmann, C. M., & Morris, S. A. (2020) · doi:10.1101/2020.02.17.947416 · Cited by 81 · see citing works
The transcriptome dynamics of single cells during the cell cycle
Schwabe, D., Formichetti, S., Junker, J. P., Falcke, M., & Rajewsky, N. (2020) · Molecular Systems Biology · doi:10.15252/msb.20209946 · Cited by 76 · see citing works
Self-citationA practical solution for preserving single cells for RNA sequencing
Attar, M., Sharma, E., Li, S., Bryer, C., Cubitt, L., Broxholme, J., Lockstone, H., Kinchen, J., Simmons, A., Piazza, P., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-20372-7 · Cited by 80 · see citing works
Rodriguez-Romaguera, J., Ung, R. L., Nomura, H., Otis, J. M., Basiri, M. L., Namboodiri, V. M. K., Zhu, X., Robinson, J. E., van den Munkhof, H. E., McHenry, J. A., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108362 · Cited by 75 · see citing works
“To fix the cells (Alles et al., 2017), 4.0 mL of ice-cold 100% methanol was added dropwise to the suspension while gently swirling the tube.”
InfluentialThe promise of single-cell RNA sequencing for kidney disease investigation
Wu, H., & Humphreys, B. D. (2017) · Kidney International · doi:10.1016/j.kint.2017.06.033 · Cited by 73 · see citing works
Waise, S., Parker, R., Rose-Zerilli, M. J. J., Layfield, D. M., Wood, O., West, J., Ottensmeier, C. H., Thomas, G. J., & Hanley, C. J. (2019) · Scientific Reports · doi:10.1038/s41598-019-45842-4 · Cited by 70 · see citing works
High-throughput RNA sequencing of paraformaldehyde-fixed single cells
Phan, H. V., van Gent, M., Drayman, N., Basu, A., Gack, M. U., & Tay, S. (2021) · Nature Communications · doi:10.1038/s41467-021-25871-2 · Cited by 64 · see citing works
CSS: cluster similarity spectrum integration of single-cell genomics data
He, Z., Brazovskaja, A., Ebert, S., Camp, J. G., & Treutlein, B. (2020) · Genome biology · doi:10.1186/s13059-020-02147-4 · Cited by 63 · see citing works
Capybara: A computational tool to measure cell identity and fate transitions
Kong, W., Fu, Y. C., Holloway, E. M., Garipler, G., Yang, X., Mazzoni, E. O., & Morris, S. A. (2022) · Cell stem cell · doi:10.1016/j.stem.2022.03.001 · Cited by 61 · see citing works
“…scRNA-seq alone to build a prediction model based on a training dataset, estimating the probability of each cell belonging to a cell type category (Alquicira-Hernandez et al., 2019); SingleCellNet is an approach that quantitatively assesses identity using a Random Forest classifier to learn cell…”
MethodTracing tumorigenesis in a solid tumor model at single-cell resolution
Praktiknjo, S. D., Obermayer, B., Zhu, Q., Fang, L., Liu, H., Quinn, H. M., Stoeckius, M., Kocks, C., Birchmeier, W., & Rajewsky, N. (2020) · Nature Communications · doi:10.1038/s41467-020-14777-0 · Cited by 60 · see citing works
Self-citationscRMD: imputation for single cell RNA-seq data via robust matrix decomposition
Chen, C., Wu, C., Wu, L., Wang, X.-C., Deng, M., & Xi, R. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa139 · Cited by 63 · see citing works
Single‐nucleus RNA sequencing of plant tissues using a nanowell‐based system
Sunaga, D. Y., Muiño, J. M., Braeuning, C., Xu, X., Zong, M., Smaczniak, C., Yan, W., Fischer, C., Vidal, R. O., Kliem, M., et al. (2021) · The Plant Journal · doi:10.1111/tpj.15458 · Cited by 63 · see citing works
“the possibility to simplify the storage of plant samples and maintaining in situ expression states (Alles et al., 2017), we”
BackgroundQuantitative single-cell transcriptomics
Ziegenhain, C., Vieth, B., Parekh, S., Hellmann, I., & Enard, W. (2018) · Briefings in Functional Genomics · doi:10.1093/bfgp/ely009 · Cited by 58 · see citing works
Single‐Cell Sequencing Methodologies: From Transcriptome to Multi‐Dimensional Measurement
Chen, Y., Song, J. T., Ruan, Q., Zeng, X., Wu, L., Cai, L., Wang, X., & Yang, C. J. (2021) · Small Methods · doi:10.1002/smtd.202100111 · Cited by 59 · see citing works
Deciphering Brain Complexity using Single-Cell Sequencing
Mu, Q., Chen, Y., & Wang, J. (2019) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2018.07.007 · Cited by 60 · see citing works
“Chemical fixation methods may also facilitate stabilization and preservation of dissociated cells for weeks before scRNA-seq, while producing comparable results as data generated from fresh samples [38].”
BackgroundResultSingle‐cell RNA sequencing in Drosophila: Technologies and applications
Li, H. (2020) · Wiley Interdisciplinary Reviews Developmental Biology · doi:10.1002/wdev.396 · Cited by 52 · see citing works
“Alles et al. (2017) showed that methanol fixation could preserve dissociated cells for several weeks without compromising scRNA-seq data quality, and this method was validated in both mouse brain cells and Drosophila embryos.”
MethodNeurovascular adaptations modulating cognition, mood, and stress responses
Dion‐Albert, L., Dudek, K., Russo, S. J., Campbell, M., & Ménard, C. (2023) · Trends in Neurosciences · doi:10.1016/j.tins.2023.01.005 · Cited by 51 · see citing works
Technology meets TILs: Deciphering T cell function in the -omics era
Hudson, W. H., & Wieland, A. (2022) · Cancer Cell · doi:10.1016/j.ccell.2022.09.011 · Cited by 53 · see citing works
Wnt activation as a therapeutic strategy in medulloblastoma
Manoranjan, B., Venugopal, C., Bakhshinyan, D., Adile, A., Richards, L. M., Kameda-Smith, M. M., Whitley, O., Dvorkin‐Gheva, A., Subapanditha, M., Savage, N. J., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17953-4 · Cited by 50 · see citing works
Human muscle-derived CLEC14A-positive cells regenerate muscle independent of PAX7
Marg, A., Escobar, H., Karaiskos, N., Grunwald, S. A., Metzler, E., Kieshauer, J., Sauer, S., Pasemann, D., Malfatti, E., Mompoint, D. M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-13650-z · Cited by 49 · see citing works
Self-citationAmamoto, R., Garcia, M., West, E. R., Choi, J., Lapan, S. W., Lane, E. A., Perrimon, N., & Cepko, C. L. (2019) · eLife · doi:10.7554/elife.51452 · Cited by 49 · see citing works
Gu, S., Olszewski, R. T., Taukulis, I., Wei, Z., Martı́n, D., Morell, R. J., & Hoa, M. (2020) · Scientific Reports · doi:10.1038/s41598-020-75238-8 · Cited by 47 · see citing works
The effect of methanol fixation on single-cell RNA sequencing data
Wang, X., Yu, L., & Wu, A. R. (2021) · BMC Genomics · doi:10.1186/s12864-021-07744-6 · Cited by 52 · see citing works
Deleersnijder, D., Callemeyn, J., Arijs, I., Naesens, M., Craenenbroeck, A. H. V., Lambrechts, D., & Sprangers, B. (2021) · Journal of the American Society of Nephrology · doi:10.1681/asn.2021020157 · Cited by 46 · see citing works
“Methanol is a coagulating fixative that does not alter the structure of nucleic acids, and dissociated, methanol-fixed cells can be frozen at 280 C and stored for several weeks.(31) To date, no studies have used methanol fixation on human kidney cells, this has only been performed in mice (Supplemental Table 3).”
BackgroundApplication of single-cell sequencing in human cancer
Rantalainen, M. (2017) · Briefings in Functional Genomics · doi:10.1093/bfgp/elx036 · Cited by 44 · see citing works
“Evaluation of a few methods for temporary storage of samples for single-cell sequencing applications, including cryopreservation [22] (DNA- or RNA-seq), methanol fixation [23] (DNA- or RNA-seq) and CellSave [24] (DNA sequencing), has recently been reported.”
BackgroundGene regulatory network reconfiguration in direct lineage reprogramming
Kamimoto, K., Adil, M. T., Jindal, K., Hoffmann, C. M., Kong, W., Yang, X., & Morris, S. A. (2023) · Stem Cell Reports · doi:10.1016/j.stemcr.2022.11.010 · Cited by 42 · see citing works
The Human Cell Atlas: Technical approaches and challenges
Hon, C.-C., Shin, J. W., Carninci, P., & Stubbington, M. J. T. (2017) · Briefings in Functional Genomics · doi:10.1093/bfgp/elx029 · Cited by 40 · see citing works
“Chemical fixation of dissociated cell suspensions before scRNAseq has been demonstrated for cells from model organisms using fixation with formaldehyde [16] or methanol [17,18] and for human embryonic stem cells and glia using formaldehyde [19].”
MethodMethods for Single-Cell Isolation and Preparation
Pensold, D., & Zimmer‐Bensch, G. (2020) · Advances in experimental medicine and biology · doi:10.1007/978-981-15-4494-1_2 · Cited by 42 · see citing works
Hinze, C., Karaiskos, N., Boltengagen, A., Walentin, K., Redo, K., Himmerkus, N., Bleich, M., Potter, S. S., Potter, A., Eckardt, K., et al. (2020) · Journal of the American Society of Nephrology · doi:10.1681/asn.2020070930 · Cited by 41 · see citing works
Self-citationSingle-Cell Computational Strategies for Lineage Reconstruction in Tissue Systems
Herring, C. A., Chen, B., McKinley, E. T., & Lau, K. S. (2018) · Cellular and Molecular Gastroenterology and Hepatology · doi:10.1016/j.jcmgh.2018.01.023 · Cited by 35 · see citing works
Jun, S., Lim, H., Chun, H., Lee, J. H., & Bang, D. (2020) · Communications Biology · doi:10.1038/s42003-020-0888-2 · Cited by 38 · see citing works
“Methanol fixation was performed as described previously(36).”
Seiler, K. M., Waye, S. E., Kong, W., Kamimoto, K., Bajinting, A., Goo, W. H., Onufer, E. J., Courtney, C. M., Guo, J., Warner, B. W., et al. (2019) · Cellular and Molecular Gastroenterology and Hepatology · doi:10.1016/j.jcmgh.2019.06.001 · Cited by 40 · see citing works
“Just before cell capture, methanol-fixed cells were placed on ice, then spun at 3000 rpm for 5 minutes at 4 C, followed by resuspension and rehydration in PBS, as previously described.(60) Resulting cDNA libraries were quantified on an Agilent Tapestation and sequenced on an Illumina HiSeq 2500.”
MethodBerrío, R. T., Verhelst, E., Eekhout, T., Grones, C., Veylder, L. D., Rybel, B. D., & Dubois, M. (2025) · New Phytologist · doi:10.1111/nph.20446 · Cited by 39 · see citing works
Cell Atlas technologies and insights into tissue architecture
Wilbrey-Clark, A., Roberts, K., & Teichmann, S. A. (2020) · Biochemical Journal · doi:10.1042/bcj20190341 · Cited by 36 · see citing works
Luff, S. A., Creamer, J. P., Valsoni, S., Dege, C., Scarfò, R., Dacunto, A., Cascione, S., Randolph, L. N., Cavalca, E., Ivan Merelli, A., et al. (2022) · Nature Cell Biology · doi:10.1038/s41556-022-00898-9 · Cited by 39 · see citing works
“Cells from each day 3 differentiation culture condition were methanol-fixed as previously described 41 .”
Single cell genomics as a transformative approach for aquaculture research and innovation
Daniels, R. R., Taylor, R. S., Robledo, D., & Macqueen, D. J. (2023) · Reviews in Aquaculture · doi:10.1111/raq.12806 · Cited by 35 · see citing works
“These include the use of fixatives including methanol 147 and formaldehyde, 46 in addition to cryopreservation in DMSO.”
MethodKim, D. W., Place, E., Chinnaiya, K., Manning, E., Sun, C., Dai, W., Groves, I., Ohyama, K., Burbridge, S., Placzek, M., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2021.110251 · Cited by 36 · see citing works
“Cells were stored at −80°C until scRNA-Seq. scRNA-seq data generation— Methanol-fixed chick embryos of dissected hypothalamus at HH8, HH8, HH13, HH15/16, HH18/19, HH20/21 were re-hydrated as previously described (Alles et al., 2017).”
Taking Insect Immunity to the Single-Cell Level
Merkling, S. H., & Lambrechts, L. (2020) · Trends in Immunology · doi:10.1016/j.it.2020.01.002 · Cited by 36 · see citing works
Channathodiyil, P., & Houseley, J. M. (2021) · PLoS ONE · doi:10.1371/journal.pone.0240769 · Cited by 32 · see citing works
“We and others routinely employ ethanol fixation on yeast prior to RNA isolation and find the fixation speed and preservation of RNA to be excellent [21, 22], while similarly high quality RNA has been isolated from methanol or ethanol-fixed mammalian cells [23-26].”
MethodKu, C., & Sebé-Pedrós, A. (2019) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0098 · Cited by 31 · see citing works
“Although most single-cell studies are performed on fresh cells, several chemicals have been employed to try to preserve native cell states in animal samples, including methanol [31], dimethylsulfoxide [32], crosslinkers that require later reverse cross-linking such as paraformaldehyde [33] and dithio-bis(succinimidyl…”
BackgroundSantiago, C. P., Gimmen, M. Y., Lu, Y., McNally, M. M., Duncan, L. H., Creamer, T. J., Orzolek, L. D., Blackshaw, S., & Singh, M. S. (2023) · Ophthalmology Science · doi:10.1016/j.xops.2023.100335 · Cited by 28 · see citing works
“Optimized dissociation protocols such as gentle papain treatment or fixative approaches such as rapid methanol fixation may be used to partially overcome this sampling bias and improve the capture efficiency of retinal neurons and rare cell types.(55,56) Furthermore, despite the greater overall efficiency of Müller gl…”
BackgroundA multi-center cross-platform single-cell RNA sequencing reference dataset
Chen, X., Yang, Z., Chen, W., Zhao, Y., Farmer, A. A., Tran, B. Q., Furtak, V. A., Moos, M. C., Xiao, W., & Wang, C. (2021) · Scientific Data · doi:10.1038/s41597-021-00809-x · Cited by 30 · see citing works
Croucher, D. C., Richards, L. M., Tsofack, S. P., Waller, D. D., Li, Z., Wei, E. N., Huang, X. F., Chesi, M., Bergsagel, P. L., Sébag, M., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26598-w · Cited by 28 · see citing works
Methods and challenges in the analysis of single-cell RNA-sequencing data
Cámara, P. G. (2017) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2017.12.007 · Cited by 29 · see citing works
van den Hurk, M., & Bardy, C. (2019) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2019.108350 · Cited by 27 · see citing works
Single-cell transcriptomics from human pancreatic islets: sample preparation matters
Bonnycastle, L. L., Gildea, D. E., Yan, T., Narisu, N., Swift, A. J., Wolfsberg, T. G., Erdos, M. R., & Collins, F. S. (2019) · Biology Methods and Protocols · doi:10.1093/biomethods/bpz019 · Cited by 27 · see citing works
“5%; Supplementary Figure S1), consistent with previous reports comparing Fresh and Fixed datasets [8, 9].”
ResultMorsey, B., Niu, M., Dyavar, S. R., Fletcher, C. V., Lamberty, B. G., Emanuel, K., Fangmeier, A., & Fox, H. S. (2021) · iScience · doi:10.1016/j.isci.2021.102357 · Cited by 25 · see citing works
Practical Considerations for Single‐Cell Genomics
Regan, C., & Preall, J. B. (2022) · Current Protocols · doi:10.1002/cpz1.498 · Cited by 25 · see citing works
“Buffers comprising PBS + 0.01% w/v bovine serum albumin or saline sodium citrate (SSC) have been compared and contrasted for various cell types, with mixed results (Alles et al., 2017a; Denisenko et al., 2020).”
BackgroundResultInfluentialGutiérrez-Franco, A., Ake, F. A., Hassan, M. N., Cayuela, N. C., Mularoni, L., & Plass, M. (2023) · Communications Biology · doi:10.1038/s42003-023-04834-x · Cited by 24 · see citing works
Chen, D., Zaid, M. I. A., Reiter, J. L., Czader, M., Wang, L., McGuire, P. C., Xuei, X., Gao, H., Huang, K., Abonour, R., et al. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.663487 · Cited by 23 · see citing works
SLAM-Drop-seq reveals mRNA kinetic rates throughout the cell cycle
Liu, H., Arsiè, R., Schwabe, D., Schilling, M., Minia, I., Alles, J., Boltengagen, A., Kocks, C., Falcke, M., Friedman, N., et al. (2023) · Molecular Systems Biology · doi:10.15252/msb.202211427 · Cited by 23 · see citing works
Self-citationRuf-zamojski, F., Ge, Y., Nair, V., Zamojski, M., Pincas, H., Toufaily, C., Tome-Garcia, J., Stoeckius, M., Stephenson, W., Smith, G. R., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky991 · Cited by 20 · see citing works
“1 M 2-mercaptoethanol) (23) and storage at −20◦C, (ii) cell fixation with 4% PFA and storage at −80◦C, as previously described (21), (iii) cell freezing in DMEM supplemented with 20% FBS and 10% DMSO, and storage at −80◦C (20) and (iv) methanol fixation and storage at −80◦C (19).”
Method
- Authors
- Alles, J., Karaiskos, N., Praktiknjo, S. D., Grosswendt, S., Wahle, P., Ruffault, P.-L., Ayoub, S., Schreyer, L., Boltengagen, A., Birchmeier, C., Zinzen, R., Kocks, C., & Rajewsky, N.
- Affiliations
- Max Delbrück Center (DE)
- Corresponding author
- Kocks, Christine
- Rajewsky, Nikolaus
- ORCID
- Venue
- BMC Biology
- Published
- 2017-05-19
- Volume
- 15
- Issue
- 1
- Pages
- 44-44
- ISSN
- 1741-7007 (ISSN-L)
- PMC
- PMC5438562
- OpenAlex
- W2950862527
- Cited by
- 218
- References
- 26
- Citations by year
- 2026: 8 · 2025: 19 · 2024: 23 · 2023: 20 · 2022: 21 · 2021: 32 · 2020: 37 · 2019: 28 · 2018: 19 · 2017: 10 · 2013: 1
- FWCI
- 10.50
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- BMC Biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Deutsche Forschungsgemeinschaft (SFB 665, cluster of excellence Neurocure)
- Deutsches Zentrum für Herz-Kreislaufforschung (DZHK BER1.2VD)
- European Molecular Biology Organization (EMBO fellowship)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Physical Sciences › Engineering › Biomedical Engineering › Innovative Microfluidic and Catalytic Techniques Innovation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- cell fixation, methanol fixation, cell preservation, single-cell RNA sequencing, Drop-seq, droplet microfluidics, Drosophila embryo, neuronal cell types
- MeSH terms
- Methanol, Animals, Cells, Cultured, Cerebellum, Drosophila, Embryo, Nonmammalian, Flow Cytometry, Humans, Rhombencephalon, RNA, Messenger, Software, Sequence Analysis, RNA, Gene Expression Profiling, Mice, Single-Cell Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
