Bayesian approach to single-cell differential expression analysis

A method to model expression variability in single-cell RNA-seq measurements and thus to improve subsequent data analysis. Single-cell data provide a means to dissect the composition of complex tissues and specialized cellular environments. However, the analysis of such measurements is complicated b...

Full description

Saved in:

Bibliographic Details
Published in	Nature methods Vol. 11; no. 7; pp. 740 - 742
Main Authors	Kharchenko, Peter V, Silberstein, Lev, Scadden, David T
Format	Journal Article
Language	English
Published	New York Nature Publishing Group US 01.07.2014 Nature Publishing Group
Subjects	38/91 631/114/2415 631/1647/2217/2218 631/208/212/2019 Algorithms Analysis Bayes Theorem Bayesian analysis Bayesian statistical decision theory Bioinformatics Biological Microscopy Biological Techniques Biomedical Engineering/Biotechnology brief-communication Cell differentiation Cellular biology Gene expression Gene Expression Profiling - methods Life Sciences Oligonucleotide Array Sequence Analysis Physiological aspects Protein expression Proteomics Ribonucleic acid RNA Sequence Analysis, RNA - methods Single-Cell Analysis - methods Subpopulations
Online Access	Get full text
ISSN	1548-7091 1548-7105 1548-7105
DOI	10.1038/nmeth.2967

Cover

Abstract	A method to model expression variability in single-cell RNA-seq measurements and thus to improve subsequent data analysis. Single-cell data provide a means to dissect the composition of complex tissues and specialized cellular environments. However, the analysis of such measurements is complicated by high levels of technical noise and intrinsic biological variability. We describe a probabilistic model of expression-magnitude distortions typical of single-cell RNA-sequencing measurements, which enables detection of differential expression signatures and identification of subpopulations of cells in a way that is more tolerant of noise.
AbstractList	Single-cell data provide a means to dissect the composition of complex tissues and specialized cellular environments. However, the analysis of such measurements is complicated by high levels of technical noise and intrinsic biological variability. We describe a probabilistic model of expression-magnitude distortions typical of single-cell RNA-sequencing measurements, which enables detection of differential expression signatures and identification of subpopulations of cells in a way that is more tolerant of noise. Single-cell data provide a means to dissect the composition of complex tissues and specialized cellular environments. However, the analysis of such measurements is complicated by high levels of technical noise and intrinsic biological variability. We describe a probabilistic model of expression-magnitude distortions typical of single-cell RNA-sequencing measurements, which enables detection of differential expression signatures and identification of subpopulations of cells in a way that is more tolerant of noise.Single-cell data provide a means to dissect the composition of complex tissues and specialized cellular environments. However, the analysis of such measurements is complicated by high levels of technical noise and intrinsic biological variability. We describe a probabilistic model of expression-magnitude distortions typical of single-cell RNA-sequencing measurements, which enables detection of differential expression signatures and identification of subpopulations of cells in a way that is more tolerant of noise. A method to model expression variability in single-cell RNA-seq measurements and thus to improve subsequent data analysis. Single-cell data provide a means to dissect the composition of complex tissues and specialized cellular environments. However, the analysis of such measurements is complicated by high levels of technical noise and intrinsic biological variability. We describe a probabilistic model of expression-magnitude distortions typical of single-cell RNA-sequencing measurements, which enables detection of differential expression signatures and identification of subpopulations of cells in a way that is more tolerant of noise. Single-cell data provides means to dissect the composition of complex tissues and specialized cellular environments. However, the analysis of such measurements is complicated by high levels of technical noise and intrinsic biological variability. We describe a probabilistic model of expression magnitude distortions typical of single-cell RNA sequencing measurements, which enables detection of differential expression signatures and identification of subpopulations of cells in a way that is more tolerant of noise.
Audience	Academic
Author	Kharchenko, Peter V Scadden, David T Silberstein, Lev
AuthorAffiliation	5 Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA 2 Hematology/Oncology Program, Children's Hospital, Boston, MA, USA 3 Harvard Stem Cell Institute, Cambridge, MA, USA 1 Center for Biomedical Informatics, Harvard Medical School, Boston, MA, USA 4 Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, USA
AuthorAffiliation_xml	– name: 3 Harvard Stem Cell Institute, Cambridge, MA, USA – name: 5 Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA – name: 1 Center for Biomedical Informatics, Harvard Medical School, Boston, MA, USA – name: 4 Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, USA – name: 2 Hematology/Oncology Program, Children's Hospital, Boston, MA, USA
Author_xml	– sequence: 1 givenname: Peter V surname: Kharchenko fullname: Kharchenko, Peter V email: peter.kharchenko@post.harvard.edu organization: Center for Biomedical Informatics, Harvard Medical School, Hematology/Oncology Program, Children's Hospital, Harvard Stem Cell Institute – sequence: 2 givenname: Lev surname: Silberstein fullname: Silberstein, Lev organization: Harvard Stem Cell Institute, Center for Regenerative Medicine, Massachusetts General Hospital, Department of Stem Cell and Regenerative Biology, Harvard University – sequence: 3 givenname: David T surname: Scadden fullname: Scadden, David T organization: Harvard Stem Cell Institute, Center for Regenerative Medicine, Massachusetts General Hospital, Department of Stem Cell and Regenerative Biology, Harvard University
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/24836921$$D View this record in MEDLINE/PubMed
BookMark	eNp9kV2P1CAUholZ437ojT_ANPHGaDpC-Wh7YzJu_Eo28UavySmFGTYUKrTq_HupM6uz68aQAIHnvHDe9xyd-OA1Qk8JXhFMm9d-0NN2VbWifoDOCGdNWRPMT272uCWn6Dyla4wpZRV_hE4r1lDRVuQMrd_CTicLvoBxjAHUtphCkazfOF0q7VzRW2N01H6y4Ar9c4w6JRsy78Htkk2P0UMDLuknh_UCfX3_7svlx_Lq84dPl-urUgnGp5L2SpiO0rbFGIOh1HRcYMMYbXvABFctMV3f1bg3DWEMuGBNz3GXJ4ErUPQCvdrrzn6E3Q9wTo7RDhB3kmC5GCF_GyEXIzL9Zk-PczfoXuX_R_hbEcDK2zfebuUmfJeMkKqqRRZ4cRCI4dus0yQHmxZDwOswJ5m9JbSpGGky-vwOeh3mmO1ZKF4LTkR9RG3AaWm9CfldtYjKNa0pr5u2ppla3UPl0evBqpy7sfn8VsGz40b_dHgTcQZe7gEVQ0pRm__bhu_Ayk4w5bzzN6y7v-SQS8q6fqPjUff_0r8AaHTWPw
CitedBy_id	crossref_primary_10_1038_s41592_024_02436_x crossref_primary_10_1002_sim_10334 crossref_primary_10_1111_aji_13157 crossref_primary_10_7554_eLife_43803 crossref_primary_10_1038_s41467_020_14976_9 crossref_primary_10_1016_j_stem_2019_09_004 crossref_primary_10_1038_s41586_019_0989_6 crossref_primary_10_1016_j_molcel_2017_01_023 crossref_primary_10_1038_s41598_023_32293_1 crossref_primary_10_1016_j_cell_2022_01_022 crossref_primary_10_1093_bfgp_elx029 crossref_primary_10_1093_bioinformatics_btaf090 crossref_primary_10_1016_j_celrep_2017_04_074 crossref_primary_10_1016_j_stemcr_2019_08_006 crossref_primary_10_1038_s41467_018_07329_0 crossref_primary_10_1093_bib_bbae511 crossref_primary_10_1016_j_compbiomed_2024_109400 crossref_primary_10_7554_eLife_88294_4 crossref_primary_10_1186_s12920_023_01549_0 crossref_primary_10_1038_s41598_021_98560_1 crossref_primary_10_12688_f1000research_7223_1 crossref_primary_10_1093_bib_bbab236 crossref_primary_10_1186_s13059_016_0927_y crossref_primary_10_15252_embj_2018100164 crossref_primary_10_1002_1873_3468_12684 crossref_primary_10_1016_j_cell_2016_03_023 crossref_primary_10_1002_1878_0261_12569 crossref_primary_10_1371_journal_pbio_2004050 crossref_primary_10_1093_bioinformatics_btw202 crossref_primary_10_1073_pnas_2209124120 crossref_primary_10_1186_s12967_020_02247_6 crossref_primary_10_1038_s41598_020_74598_5 crossref_primary_10_1093_bioinformatics_btaa1078 crossref_primary_10_1186_s13059_024_03351_2 crossref_primary_10_1038_s41592_020_0854_4 crossref_primary_10_7554_eLife_51413 crossref_primary_10_1093_biostatistics_kxx053 crossref_primary_10_1093_nar_gkab601 crossref_primary_10_1016_j_ymeth_2020_09_010 crossref_primary_10_1016_j_ymeth_2018_04_017 crossref_primary_10_1093_bfgp_elx036 crossref_primary_10_1002_wdev_368 crossref_primary_10_3390_ijms20225773 crossref_primary_10_1371_journal_pone_0232271 crossref_primary_10_3390_genes14020403 crossref_primary_10_1002_wics_1558 crossref_primary_10_1016_j_neuron_2015_10_007 crossref_primary_10_1016_j_xcrm_2024_101420 crossref_primary_10_1002_gcc_22944 crossref_primary_10_3389_fimmu_2023_1239148 crossref_primary_10_1007_s40484_019_0189_2 crossref_primary_10_1093_bioinformatics_bty640 crossref_primary_10_3390_molecules24010042 crossref_primary_10_2139_ssrn_3867727 crossref_primary_10_1038_ncb3493 crossref_primary_10_1016_j_compbiomed_2021_104374 crossref_primary_10_1093_bib_bbz063 crossref_primary_10_1109_TCBB_2022_3203592 crossref_primary_10_1038_nbt_3711 crossref_primary_10_1038_s41467_024_55500_7 crossref_primary_10_1093_bioinformatics_btz726 crossref_primary_10_1007_s00418_016_1466_z crossref_primary_10_3389_fonc_2022_857037 crossref_primary_10_1038_nmicrobiol_2016_206 crossref_primary_10_1038_ncomms14219 crossref_primary_10_1093_bib_bbaa347 crossref_primary_10_1186_s12864_021_08235_4 crossref_primary_10_1038_nbt_3701 crossref_primary_10_1039_C9ME00029A crossref_primary_10_1016_j_coisb_2017_12_007 crossref_primary_10_1093_bioinformatics_btw248 crossref_primary_10_1016_j_ccell_2016_10_005 crossref_primary_10_1016_j_bspc_2023_105785 crossref_primary_10_1134_S0006297923020074 crossref_primary_10_1142_S0219720020400053 crossref_primary_10_1093_bioinformatics_btz752 crossref_primary_10_1093_gigascience_giz106 crossref_primary_10_1038_s12276_020_0422_0 crossref_primary_10_1186_s12864_024_10364_5 crossref_primary_10_1016_j_gpb_2022_04_001 crossref_primary_10_1007_s11427_021_2119_5 crossref_primary_10_1038_s42256_022_00534_z crossref_primary_10_1093_bioinformatics_btaa467 crossref_primary_10_1186_s40246_024_00638_0 crossref_primary_10_1093_molbev_msaf004 crossref_primary_10_3389_fgene_2019_01387 crossref_primary_10_1093_bib_bbab460 crossref_primary_10_1186_s12859_023_05424_8 crossref_primary_10_3390_ijms26052074 crossref_primary_10_1016_j_devcel_2018_01_006 crossref_primary_10_1016_j_copbio_2019_03_001 crossref_primary_10_1186_s12859_019_2977_0 crossref_primary_10_1038_s41598_019_41235_9 crossref_primary_10_1093_nargab_lqad018 crossref_primary_10_1093_molbev_msz290 crossref_primary_10_1016_j_conb_2017_10_005 crossref_primary_10_1158_1541_7786_MCR_20_0051 crossref_primary_10_59368_agingbio_20230008 crossref_primary_10_3389_fcell_2020_588041 crossref_primary_10_1016_j_kint_2017_06_033 crossref_primary_10_1080_15476286_2021_1960688 crossref_primary_10_1093_bioinformatics_btab337 crossref_primary_10_1093_nar_gkac317 crossref_primary_10_1186_s13059_019_1850_9 crossref_primary_10_1016_j_stem_2019_07_009 crossref_primary_10_3390_cells12151970 crossref_primary_10_3389_fgene_2016_00163 crossref_primary_10_1186_s12859_022_04814_8 crossref_primary_10_3389_fpls_2018_01646 crossref_primary_10_1101_gr_267070_120 crossref_primary_10_1002_pros_24460 crossref_primary_10_3389_fnins_2021_591122 crossref_primary_10_1038_s41598_017_13665_w crossref_primary_10_18632_oncotarget_17893 crossref_primary_10_1109_TCBB_2017_2763946 crossref_primary_10_1186_s13059_018_1575_1 crossref_primary_10_1210_endocr_bqae057 crossref_primary_10_1007_s11427_023_2561_0 crossref_primary_10_1186_s12915_021_01076_3 crossref_primary_10_1016_j_gpb_2018_08_003 crossref_primary_10_1515_sagmb_2019_0004 crossref_primary_10_1093_braincomms_fcae202 crossref_primary_10_1016_j_jhep_2022_01_014 crossref_primary_10_1158_2159_8290_CD_18_0710 crossref_primary_10_1038_s41551_021_00703_2 crossref_primary_10_1186_s13059_016_1033_x crossref_primary_10_1007_s42979_023_02215_z crossref_primary_10_1016_j_isci_2023_107472 crossref_primary_10_1186_s13059_020_01981_w crossref_primary_10_3389_fcell_2022_884748 crossref_primary_10_1038_s41467_024_50612_6 crossref_primary_10_1186_s12864_023_09487_y crossref_primary_10_1016_j_cels_2019_03_010 crossref_primary_10_1109_ACCESS_2024_3394038 crossref_primary_10_1093_nargab_lqad024 crossref_primary_10_1016_j_devcel_2015_10_011 crossref_primary_10_1093_bioinformatics_btad776 crossref_primary_10_1186_s12864_024_10976_x crossref_primary_10_1016_j_cell_2024_10_011 crossref_primary_10_3389_pore_2022_1610342 crossref_primary_10_1007_s10463_022_00835_5 crossref_primary_10_15252_msb_202110255 crossref_primary_10_1038_s41598_019_48771_4 crossref_primary_10_2174_011574888X265479231127065541 crossref_primary_10_1038_ni_3368 crossref_primary_10_3389_fgene_2019_01331 crossref_primary_10_3390_ijms25073828 crossref_primary_10_1093_bioinformatics_btaa278 crossref_primary_10_3389_fgene_2019_00009 crossref_primary_10_1158_2767_9764_CRC_23_0566 crossref_primary_10_3390_app13137936 crossref_primary_10_1371_journal_pcbi_1009118 crossref_primary_10_1007_s12539_020_00386_4 crossref_primary_10_1038_s41467_019_14198_8 crossref_primary_10_1101_gr_234062_117 crossref_primary_10_1109_TCBB_2021_3098394 crossref_primary_10_1186_s13059_021_02281_7 crossref_primary_10_1093_bioinformatics_btaa283 crossref_primary_10_1038_nn_4366 crossref_primary_10_1101_gr_275430_121 crossref_primary_10_7554_eLife_45105 crossref_primary_10_1093_bioinformatics_btz321 crossref_primary_10_1016_j_ajhg_2025_02_014 crossref_primary_10_1016_j_compbiomed_2022_105578 crossref_primary_10_1016_j_stem_2018_11_023 crossref_primary_10_1093_molehr_gav050 crossref_primary_10_1016_j_neuron_2020_12_010 crossref_primary_10_1186_s13059_024_03436_y crossref_primary_10_1073_pnas_1721085115 crossref_primary_10_1093_bioinformatics_btad325 crossref_primary_10_3390_diagnostics8020031 crossref_primary_10_1038_s41590_021_00958_6 crossref_primary_10_1038_s41584_023_01007_2 crossref_primary_10_7554_eLife_59733 crossref_primary_10_1126_science_aaq1736 crossref_primary_10_1214_21_AOAS1442 crossref_primary_10_1038_s41598_017_07746_z crossref_primary_10_1016_j_it_2016_12_001 crossref_primary_10_1093_bioinformatics_bty498 crossref_primary_10_1186_s13059_019_1874_1 crossref_primary_10_1109_TCBB_2022_3230098 crossref_primary_10_2197_ipsjtbio_17_48 crossref_primary_10_1038_s41467_024_45198_y crossref_primary_10_1371_journal_pone_0299358 crossref_primary_10_1038_s41467_019_12293_4 crossref_primary_10_1109_TCBB_2020_3025804 crossref_primary_10_1165_rcmb_2019_0297OC crossref_primary_10_1016_j_isci_2023_106792 crossref_primary_10_1186_s13059_017_1385_x crossref_primary_10_3390_ijms22031399 crossref_primary_10_3389_fncel_2017_00376 crossref_primary_10_1038_s41592_021_01344_8 crossref_primary_10_1186_s13059_016_0964_6 crossref_primary_10_1016_j_ecosta_2024_02_001 crossref_primary_10_1161_CIRCULATIONAHA_121_054744 crossref_primary_10_1038_s42003_024_06823_0 crossref_primary_10_1186_s12864_020_6502_7 crossref_primary_10_3390_genes12121947 crossref_primary_10_1186_s12864_016_2897_6 crossref_primary_10_1038_s41588_021_00873_4 crossref_primary_10_1038_s12276_020_0409_x crossref_primary_10_1016_j_gpb_2018_07_007 crossref_primary_10_1038_nbt_3192 crossref_primary_10_1038_srep31851 crossref_primary_10_1093_bioinformatics_btz240 crossref_primary_10_2139_ssrn_4047247 crossref_primary_10_1186_s12859_021_04493_x crossref_primary_10_1186_s12864_020_07007_w crossref_primary_10_1111_biom_13074 crossref_primary_10_1186_s12859_018_2092_7 crossref_primary_10_1007_s00018_019_03378_w crossref_primary_10_1038_s43588_021_00030_1 crossref_primary_10_1093_gigascience_giac126 crossref_primary_10_1038_nmeth_4263 crossref_primary_10_1186_s13059_018_1571_5 crossref_primary_10_3390_bios12070450 crossref_primary_10_3390_ijms24076229 crossref_primary_10_1093_bfgp_elac019 crossref_primary_10_1101_gr_198044_115 crossref_primary_10_1016_j_tig_2015_07_003 crossref_primary_10_1016_j_devcel_2024_12_031 crossref_primary_10_7554_eLife_42015 crossref_primary_10_1016_j_cell_2017_10_023 crossref_primary_10_1002_cpmb_92 crossref_primary_10_1111_febs_14613 crossref_primary_10_1111_imm_13460 crossref_primary_10_1126_sciimmunol_aan8664 crossref_primary_10_1186_s12967_024_05051_8 crossref_primary_10_3390_diagnostics15030252 crossref_primary_10_1186_s12859_021_04033_7 crossref_primary_10_1038_s41467_020_17929_4 crossref_primary_10_1016_j_stem_2016_07_004 crossref_primary_10_1093_bioinformatics_btz024 crossref_primary_10_1109_TCBB_2020_2979717 crossref_primary_10_3390_cells9091938 crossref_primary_10_1016_j_cels_2019_05_003 crossref_primary_10_1093_bioinformatics_btac171 crossref_primary_10_1002_cpmo_30 crossref_primary_10_1093_biolre_ioac061 crossref_primary_10_1186_s12967_023_04102_w crossref_primary_10_1002_JLB_5MR1019_179R crossref_primary_10_1101_gr_217331_116 crossref_primary_10_1016_j_csbj_2020_09_014 crossref_primary_10_1016_j_ygeno_2019_02_014 crossref_primary_10_1093_bioinformatics_btz296 crossref_primary_10_1093_bioinformatics_btae599 crossref_primary_10_1371_journal_pone_0209648 crossref_primary_10_3389_fmed_2018_00034 crossref_primary_10_1093_nar_gkx1113 crossref_primary_10_1371_journal_pcbi_1006245 crossref_primary_10_1038_nmeth_4292 crossref_primary_10_1038_s41467_024_44823_0 crossref_primary_10_1016_j_cell_2018_09_006 crossref_primary_10_1158_1541_7786_MCR_17_0776 crossref_primary_10_1186_s13045_017_0401_7 crossref_primary_10_1186_s13059_020_02132_x crossref_primary_10_1101_gr_230771_117 crossref_primary_10_1093_nar_gkz826 crossref_primary_10_1093_bfgp_elae023 crossref_primary_10_15252_embr_201846635 crossref_primary_10_1016_j_bbagrm_2015_08_005 crossref_primary_10_1002_cpmb_57 crossref_primary_10_1186_s13059_019_1806_0 crossref_primary_10_1093_bib_bbae068 crossref_primary_10_3389_fgene_2019_00500 crossref_primary_10_12688_f1000research_74416_1 crossref_primary_10_1152_ajpcell_00140_2022 crossref_primary_10_12688_f1000research_74416_2 crossref_primary_10_1172_jci_insight_151621 crossref_primary_10_1186_s13059_016_1077_y crossref_primary_10_1111_cts_12536 crossref_primary_10_1186_s13073_017_0492_3 crossref_primary_10_1007_s10565_017_9418_5 crossref_primary_10_1681_ASN_0000000000000354 crossref_primary_10_7554_eLife_12845 crossref_primary_10_1038_s41587_023_01863_z crossref_primary_10_1007_s12539_025_00688_5 crossref_primary_10_1016_j_yjmcc_2020_08_010 crossref_primary_10_1038_s41467_024_46413_6 crossref_primary_10_1186_s13059_024_03334_3 crossref_primary_10_1002_cpz1_544 crossref_primary_10_1007_s11426_023_1793_7 crossref_primary_10_1016_j_gpb_2020_11_006 crossref_primary_10_1186_s40779_021_00336_1 crossref_primary_10_1016_j_isci_2020_101485 crossref_primary_10_7717_peerj_14706 crossref_primary_10_1016_j_yexcr_2018_08_003 crossref_primary_10_1038_s41388_024_03074_5 crossref_primary_10_1242_dev_167833 crossref_primary_10_1016_j_cell_2017_11_011 crossref_primary_10_1016_j_isci_2024_109027 crossref_primary_10_1038_s41467_020_15298_6 crossref_primary_10_1515_mper_2016_0035 crossref_primary_10_32604_biocell_2022_018960 crossref_primary_10_1109_ACCESS_2020_2977106 crossref_primary_10_1038_nn_3881 crossref_primary_10_1101_gr_271288_120 crossref_primary_10_1186_s12859_018_2217_z crossref_primary_10_3389_fgene_2022_1063130 crossref_primary_10_1186_s12859_021_04412_0 crossref_primary_10_1038_s41598_020_69026_7 crossref_primary_10_1038_s41592_019_0353_7 crossref_primary_10_1038_s41467_019_12924_w crossref_primary_10_1093_bib_bbad384 crossref_primary_10_1017_S003118202100041X crossref_primary_10_1186_s12859_016_0944_6 crossref_primary_10_1016_j_isci_2022_105102 crossref_primary_10_1016_j_compbiolchem_2022_107733 crossref_primary_10_1097_JBR_0000000000000053 crossref_primary_10_1007_s00335_021_09936_7 crossref_primary_10_1111_biom_13457 crossref_primary_10_1371_journal_pcbi_1007794 crossref_primary_10_1109_ACCESS_2021_3052923 crossref_primary_10_3390_biology13070512 crossref_primary_10_1128_mBio_01037_20 crossref_primary_10_1093_bioinformatics_btw607 crossref_primary_10_1371_journal_pone_0180583 crossref_primary_10_1093_bib_bbae254 crossref_primary_10_1186_s13059_020_02116_x crossref_primary_10_1242_dmm_044404 crossref_primary_10_1101_cshperspect_a026898 crossref_primary_10_1038_s41467_021_21038_1 crossref_primary_10_1042_BST20210863 crossref_primary_10_1002_jcb_30134 crossref_primary_10_1109_TCBB_2024_3382147 crossref_primary_10_1016_j_exphem_2021_05_001 crossref_primary_10_7554_eLife_27041 crossref_primary_10_1186_s13059_020_02103_2 crossref_primary_10_1016_j_csbj_2014_09_004 crossref_primary_10_1093_bioadv_vbaf011 crossref_primary_10_1016_j_celrep_2018_11_056 crossref_primary_10_3389_fbinf_2023_1120290 crossref_primary_10_3389_fgene_2023_1215232 crossref_primary_10_1242_dev_158501 crossref_primary_10_1016_j_cels_2018_10_015 crossref_primary_10_1007_s12551_023_01091_4 crossref_primary_10_1109_TCBB_2023_3241129 crossref_primary_10_26508_lsa_202000867 crossref_primary_10_1016_j_celrep_2018_12_044 crossref_primary_10_1038_s42003_020_01364_8 crossref_primary_10_1016_j_cell_2018_06_025 crossref_primary_10_1093_nar_gkz655 crossref_primary_10_1038_s41587_020_0469_4 crossref_primary_10_1073_pnas_1912459116 crossref_primary_10_1038_s41598_022_06834_z crossref_primary_10_1016_j_ejca_2021_03_005 crossref_primary_10_1016_j_devcel_2020_06_013 crossref_primary_10_7554_eLife_30657 crossref_primary_10_1214_19_STS714 crossref_primary_10_1038_nature25999 crossref_primary_10_1186_s13059_016_0931_2 crossref_primary_10_1007_s00439_020_02116_8 crossref_primary_10_1186_s12918_018_0638_y crossref_primary_10_3390_math9192515 crossref_primary_10_1002_JLB_6MR0720_131R crossref_primary_10_1016_j_cels_2019_07_012 crossref_primary_10_1038_s41467_020_14551_2 crossref_primary_10_1093_bioinformatics_btaa607 crossref_primary_10_12688_wellcomeopenres_11087_1 crossref_primary_10_1186_s13024_022_00517_z crossref_primary_10_1182_blood_2019004547 crossref_primary_10_1186_s13059_020_1926_6 crossref_primary_10_1093_nar_gky308 crossref_primary_10_1186_s13059_019_1739_7 crossref_primary_10_1016_j_xops_2021_100010 crossref_primary_10_1093_bioinformatics_btaf074 crossref_primary_10_1038_s41598_018_34688_x crossref_primary_10_1016_j_csbj_2021_05_055 crossref_primary_10_3389_fnins_2018_00031 crossref_primary_10_1002_1873_3468_15009 crossref_primary_10_1002_cbin_11928 crossref_primary_10_1101_gr_225979_117 crossref_primary_10_1038_srep37137 crossref_primary_10_1016_j_imlet_2022_04_008 crossref_primary_10_1016_j_gpb_2016_01_005 crossref_primary_10_1371_journal_pcbi_1005562 crossref_primary_10_2139_ssrn_3596586 crossref_primary_10_1016_j_cels_2017_03_010 crossref_primary_10_1002_stem_3336 crossref_primary_10_1093_bioadv_vbad030 crossref_primary_10_1186_s12859_018_2226_y crossref_primary_10_1016_j_compbiolchem_2021_107512 crossref_primary_10_31083_j_fbl2710295 crossref_primary_10_1007_s12551_019_00499_1 crossref_primary_10_1093_bib_bbac223 crossref_primary_10_1093_bib_bbac464 crossref_primary_10_1016_j_csbj_2023_03_036 crossref_primary_10_1158_0008_5472_CAN_17_1924 crossref_primary_10_1186_s13059_020_1949_z crossref_primary_10_1016_j_matbio_2020_04_004 crossref_primary_10_1145_3632905 crossref_primary_10_1016_j_ynstr_2021_100408 crossref_primary_10_1038_s41581_021_00463_x crossref_primary_10_1128_mBio_01001_18 crossref_primary_10_1186_s13059_022_02601_5 crossref_primary_10_3389_ftox_2022_821116 crossref_primary_10_7554_eLife_38579 crossref_primary_10_1038_s41467_018_03843_3 crossref_primary_10_1016_j_tplants_2024_03_010 crossref_primary_10_1186_s12860_019_0199_y crossref_primary_10_1093_bioinformatics_btw777 crossref_primary_10_1016_j_csbj_2022_08_003 crossref_primary_10_1038_s41467_020_16019_9 crossref_primary_10_20517_2394_5079_2024_138 crossref_primary_10_1016_j_kint_2018_05_003 crossref_primary_10_1016_j_cell_2015_10_039 crossref_primary_10_1038_s41467_017_00244_w crossref_primary_10_1038_nmeth_3734 crossref_primary_10_1038_s41467_017_02554_5 crossref_primary_10_3389_fgene_2020_00295 crossref_primary_10_7717_peerj_2888 crossref_primary_10_1016_j_tins_2021_11_001 crossref_primary_10_1016_j_cub_2015_01_034 crossref_primary_10_4236_jamp_2016_47127 crossref_primary_10_1214_20_AOAS1416 crossref_primary_10_1002_sim_9603 crossref_primary_10_1016_j_stem_2022_01_010 crossref_primary_10_1016_j_devcel_2016_06_014 crossref_primary_10_1038_nrg3833 crossref_primary_10_1038_s41467_023_36062_6 crossref_primary_10_1093_bib_bbab148 crossref_primary_10_1038_s41467_020_18976_7 crossref_primary_10_7554_eLife_38314 crossref_primary_10_1038_s41467_024_55610_2 crossref_primary_10_1186_s12859_017_1647_3 crossref_primary_10_1038_s41598_023_39995_6 crossref_primary_10_1093_nargab_lqaa039 crossref_primary_10_1093_bioinformatics_btw798 crossref_primary_10_1080_01621459_2021_1886106 crossref_primary_10_1038_s41467_018_07261_3 crossref_primary_10_1016_j_ygeno_2020_01_014 crossref_primary_10_1016_j_isci_2021_102393 crossref_primary_10_1186_s12915_017_0453_8 crossref_primary_10_1093_bfgp_ely009 crossref_primary_10_1093_bioinformatics_btx435 crossref_primary_10_1093_bioinformatics_btaa318 crossref_primary_10_1214_17_AOAS1123 crossref_primary_10_1016_j_cell_2020_04_035 crossref_primary_10_1093_gigascience_giy117 crossref_primary_10_1186_s12864_019_5747_5 crossref_primary_10_3389_fgene_2017_00062 crossref_primary_10_1016_j_conb_2016_11_001 crossref_primary_10_3389_fnmol_2019_00316 crossref_primary_10_1038_s41467_021_25089_2 crossref_primary_10_1093_bib_bbab325 crossref_primary_10_1016_j_stemcr_2016_02_005 crossref_primary_10_1038_nmeth_4612 crossref_primary_10_1093_bib_bbac412 crossref_primary_10_1186_s13059_021_02367_2 crossref_primary_10_1016_j_xcrm_2024_101535 crossref_primary_10_1186_s12859_023_05349_2 crossref_primary_10_1186_s13059_018_1438_9 crossref_primary_10_1093_bioinformatics_bty517 crossref_primary_10_1007_s10815_023_02892_y crossref_primary_10_1214_17_AOAS1110 crossref_primary_10_1016_j_csbj_2023_12_021 crossref_primary_10_1016_j_celrep_2020_107724 crossref_primary_10_1016_j_plantsci_2022_111486 crossref_primary_10_1038_s41467_021_25189_z crossref_primary_10_1016_j_gpb_2020_09_006 crossref_primary_10_1371_journal_pcbi_1009064 crossref_primary_10_3389_fgene_2022_952649 crossref_primary_10_1186_s13059_020_02104_1 crossref_primary_10_1093_jmcb_mjaa053 crossref_primary_10_1007_s12561_022_09344_8 crossref_primary_10_1093_jmcb_mjaa052 crossref_primary_10_1109_TBDATA_2016_2643683 crossref_primary_10_1186_s13578_022_00886_4 crossref_primary_10_1038_s41592_019_0654_x crossref_primary_10_1016_j_bbagrm_2019_194430 crossref_primary_10_1186_s13059_020_02128_7 crossref_primary_10_1016_j_jcyt_2024_10_009 crossref_primary_10_1111_cpr_13128 crossref_primary_10_1016_j_cub_2022_07_038 crossref_primary_10_1016_j_talanta_2021_122689 crossref_primary_10_1093_bioinformatics_btaa576 crossref_primary_10_1093_bib_bbad529 crossref_primary_10_1093_bib_bbab105 crossref_primary_10_1093_bib_bbab345 crossref_primary_10_1242_dev_202778 crossref_primary_10_1186_s13059_016_0937_9 crossref_primary_10_1038_nbt_3854 crossref_primary_10_1038_s41540_022_00246_5 crossref_primary_10_1093_bib_bby076 crossref_primary_10_1016_j_isci_2021_103292 crossref_primary_10_1186_s13059_023_02897_x crossref_primary_10_1093_bioinformatics_btae703 crossref_primary_10_1242_dev_133058 crossref_primary_10_1093_bib_bbab343 crossref_primary_10_1186_s12859_020_3450_9 crossref_primary_10_1534_genetics_117_300467 crossref_primary_10_1016_j_coisb_2021_100375 crossref_primary_10_1172_jci_insight_123637 crossref_primary_10_1038_s41576_018_0088_9 crossref_primary_10_1016_j_stem_2016_10_003 crossref_primary_10_1093_bib_bbaa248 crossref_primary_10_1038_s41467_018_07165_2 crossref_primary_10_1038_s41467_020_16597_8 crossref_primary_10_4049_jimmunol_1601424 crossref_primary_10_1016_j_biopha_2023_115077 crossref_primary_10_1186_s40779_022_00434_8 crossref_primary_10_1038_ncomms14362 crossref_primary_10_1093_bioinformatics_bty329 crossref_primary_10_3389_fimmu_2021_681710 crossref_primary_10_1093_bib_bbab531 crossref_primary_10_1016_j_celrep_2019_10_073 crossref_primary_10_1016_j_celrep_2020_108447 crossref_primary_10_1093_bioinformatics_btae711 crossref_primary_10_1016_j_molcel_2021_12_012 crossref_primary_10_1016_j_neuron_2021_08_005 crossref_primary_10_1111_jnc_15250 crossref_primary_10_1186_s13059_016_1010_4 crossref_primary_10_1038_s41598_017_09307_w crossref_primary_10_1109_TCBB_2024_3492384 crossref_primary_10_2139_ssrn_4093540 crossref_primary_10_1038_ncomms14126 crossref_primary_10_1016_j_scr_2018_01_015 crossref_primary_10_7554_eLife_81810 crossref_primary_10_1093_bioinformatics_bty316 crossref_primary_10_1161_CIRCRESAHA_117_310910 crossref_primary_10_1101_gr_278843_123 crossref_primary_10_1016_j_compbiomed_2022_105658 crossref_primary_10_1093_bioinformatics_btab455 crossref_primary_10_1186_s12864_017_3893_1 crossref_primary_10_3389_fgene_2019_00317 crossref_primary_10_3390_cancers11121910 crossref_primary_10_1016_j_cell_2020_11_028 crossref_primary_10_1371_journal_pcbi_1009029 crossref_primary_10_1186_s12859_020_03547_w crossref_primary_10_1093_nar_gkaa264 crossref_primary_10_1016_j_omtm_2022_12_014 crossref_primary_10_1002_gepi_22361 crossref_primary_10_1093_bioinformatics_btaa139 crossref_primary_10_1016_j_celrep_2016_12_060 crossref_primary_10_1016_j_celrep_2016_12_066 crossref_primary_10_1016_j_compbiomed_2024_108049 crossref_primary_10_1038_nrc_2017_58 crossref_primary_10_1016_j_patter_2020_100139 crossref_primary_10_1002_anie_201709719 crossref_primary_10_1038_s41467_018_07931_2 crossref_primary_10_1007_s11033_024_09553_y crossref_primary_10_1038_nmeth_4634 crossref_primary_10_1093_nar_gkv1525 crossref_primary_10_1038_s41388_022_02478_5 crossref_primary_10_1186_s12864_020_07302_6 crossref_primary_10_1373_clinchem_2017_283895 crossref_primary_10_1016_j_csbj_2020_06_033 crossref_primary_10_1080_01621459_2017_1341412 crossref_primary_10_1016_j_devcel_2020_01_023 crossref_primary_10_1016_j_celrep_2021_108735 crossref_primary_10_1093_bioinformatics_bty332 crossref_primary_10_1038_srep33892 crossref_primary_10_1038_s41576_021_00341_z crossref_primary_10_15252_embj_2021108605 crossref_primary_10_1016_j_celrep_2019_02_053 crossref_primary_10_3390_app122010684 crossref_primary_10_1038_nbt_4096 crossref_primary_10_1016_j_celrep_2016_12_040 crossref_primary_10_1038_ni_3247 crossref_primary_10_1155_2018_4809673 crossref_primary_10_1038_nn_4495 crossref_primary_10_1093_nargab_lqaa064 crossref_primary_10_1186_s12920_018_0433_z crossref_primary_10_1053_j_gastro_2019_08_019 crossref_primary_10_1093_bioinformatics_btab003 crossref_primary_10_1093_bioinformatics_btz453 crossref_primary_10_1016_j_cell_2020_05_006 crossref_primary_10_1038_s44320_024_00045_6 crossref_primary_10_1016_j_jgg_2017_03_001 crossref_primary_10_3389_fgene_2021_648898 crossref_primary_10_1016_j_crmeth_2021_100133 crossref_primary_10_1038_s41467_020_14319_8 crossref_primary_10_1109_ACCESS_2020_3022718 crossref_primary_10_1016_j_celrep_2017_09_039 crossref_primary_10_1177_0271678X241305914 crossref_primary_10_1186_s13059_015_0805_z crossref_primary_10_1109_TCBB_2021_3128576 crossref_primary_10_1093_gigascience_giad097 crossref_primary_10_1038_s41587_023_01686_y crossref_primary_10_1093_gigascience_giad098 crossref_primary_10_1214_20_STS792 crossref_primary_10_1038_s41467_021_26779_7 crossref_primary_10_1038_nmeth_3370 crossref_primary_10_1089_cmb_2021_0051 crossref_primary_10_1214_21_AOAS1534 crossref_primary_10_1038_s41598_017_15525_z crossref_primary_10_1038_s41596_018_0073_y crossref_primary_10_1038_s41581_018_0021_7 crossref_primary_10_1093_biostatistics_kxw055 crossref_primary_10_1371_journal_pone_0210571 crossref_primary_10_1038_s41586_018_0345_2 crossref_primary_10_1186_s12859_023_05432_8 crossref_primary_10_12677_BP_2023_131008 crossref_primary_10_3390_ijms232012142 crossref_primary_10_1093_bib_bbw057 crossref_primary_10_1016_j_gde_2017_01_003 crossref_primary_10_1002_btpr_2264 crossref_primary_10_3389_fimmu_2018_01553 crossref_primary_10_1038_s12276_023_01043_8 crossref_primary_10_1137_19M1253198 crossref_primary_10_1016_j_csbj_2025_03_033 crossref_primary_10_1016_j_copbio_2016_03_015 crossref_primary_10_1038_s41587_022_01288_0 crossref_primary_10_1186_s12859_020_03641_z crossref_primary_10_1016_j_coi_2020_02_004 crossref_primary_10_1109_TCBB_2018_2848633 crossref_primary_10_1093_toxsci_kfab065 crossref_primary_10_1038_s41467_024_46773_z crossref_primary_10_15252_embr_201949555 crossref_primary_10_1007_s40484_016_0089_7 crossref_primary_10_1186_s13059_018_1498_x crossref_primary_10_12688_f1000research_13511_1 crossref_primary_10_12688_f1000research_13511_2 crossref_primary_10_12688_f1000research_13511_3 crossref_primary_10_3390_cells8070698 crossref_primary_10_1080_02664763_2018_1437123 crossref_primary_10_1186_s13059_023_02933_w crossref_primary_10_1038_s41467_024_50150_1 crossref_primary_10_1371_journal_pcbi_1008569 crossref_primary_10_1038_s41592_019_0372_4 crossref_primary_10_1093_bfgp_elad011 crossref_primary_10_3389_fgene_2022_867880 crossref_primary_10_1101_gr_223313_117 crossref_primary_10_1016_j_cels_2017_08_014 crossref_primary_10_1109_TCBB_2019_2893170 crossref_primary_10_1038_s41592_018_0303_9 crossref_primary_10_1039_C4IB00192C crossref_primary_10_1038_s12276_018_0071_8 crossref_primary_10_1038_s41467_018_04629_3 crossref_primary_10_1109_JBHI_2021_3050963 crossref_primary_10_1101_gr_207704_116 crossref_primary_10_1214_22_AOAS1689 crossref_primary_10_1093_bioinformatics_btaa098 crossref_primary_10_1186_s13073_022_01097_9 crossref_primary_10_1186_s13059_021_02548_z crossref_primary_10_1016_j_tranon_2024_101879 crossref_primary_10_1186_s12864_019_5970_0 crossref_primary_10_1016_j_coisb_2017_07_013 crossref_primary_10_15252_msb_20166969 crossref_primary_10_3390_pathogens10111467 crossref_primary_10_7554_eLife_88294 crossref_primary_10_1038_s41587_021_00895_7 crossref_primary_10_17749_2070_4909_farmakoekonomika_2023_169 crossref_primary_10_1038_s41592_018_0229_2 crossref_primary_10_1186_s13059_016_0930_3 crossref_primary_10_1093_bioinformatics_btac288 crossref_primary_10_1038_nprot_2017_120 crossref_primary_10_1164_rccm_202003_0541OC crossref_primary_10_18632_aging_206105 crossref_primary_10_1016_j_celrep_2016_06_059 crossref_primary_10_3892_ijo_2019_4897 crossref_primary_10_1093_biomet_asac029 crossref_primary_10_15252_msb_20188746 crossref_primary_10_1038_nature22991 crossref_primary_10_1038_s43588_024_00734_0 crossref_primary_10_1002_jcp_26303 crossref_primary_10_3389_fimmu_2023_1058296 crossref_primary_10_1016_j_virusres_2016_10_016 crossref_primary_10_1096_fj_201901314RR crossref_primary_10_1161_CIRCRESAHA_124_324328 crossref_primary_10_1093_bioinformatics_btz177 crossref_primary_10_1093_nar_gkx754 crossref_primary_10_1016_j_cell_2017_03_050 crossref_primary_10_1186_s12918_016_0370_4 crossref_primary_10_1093_narcan_zcaa011 crossref_primary_10_1016_j_cell_2020_07_017 crossref_primary_10_1038_s41592_019_0494_8 crossref_primary_10_1016_j_apm_2020_08_065 crossref_primary_10_1093_bib_bbad062 crossref_primary_10_1186_s12859_016_1235_y crossref_primary_10_3390_biom12081130 crossref_primary_10_1371_journal_pcbi_1005016 crossref_primary_10_1016_j_cell_2017_08_024 crossref_primary_10_1002_jcb_27066 crossref_primary_10_1093_bioinformatics_bty1044 crossref_primary_10_1038_s41598_022_06500_4 crossref_primary_10_3389_fimmu_2019_02568 crossref_primary_10_1109_ACCESS_2020_3001986 crossref_primary_10_1093_nar_gkw430 crossref_primary_10_2139_ssrn_3189384 crossref_primary_10_31857_S032097252302001X crossref_primary_10_1038_s41592_019_0690_6 crossref_primary_10_26508_lsa_202302126 crossref_primary_10_1016_j_gpb_2020_05_005 crossref_primary_10_1158_1541_7786_MCR_18_1054 crossref_primary_10_1038_s43588_021_00099_8 crossref_primary_10_1016_j_celrep_2019_03_104 crossref_primary_10_1093_bioinformatics_bty1016 crossref_primary_10_1126_science_aba3203 crossref_primary_10_1186_s12864_021_07744_6 crossref_primary_10_1101_gr_228080_117 crossref_primary_10_1038_nmeth_4150 crossref_primary_10_1016_j_stem_2021_03_021 crossref_primary_10_1038_srep23270 crossref_primary_10_1186_s13059_017_1188_0 crossref_primary_10_1186_s13059_022_02682_2 crossref_primary_10_1093_molbev_msx336 crossref_primary_10_3389_fcvm_2019_00173 crossref_primary_10_1186_s12859_019_2599_6 crossref_primary_10_1038_nmeth_3076 crossref_primary_10_3390_genes13020377 crossref_primary_10_1038_s41568_023_00549_7 crossref_primary_10_1186_s13059_022_02605_1 crossref_primary_10_7554_eLife_18683 crossref_primary_10_1073_pnas_1820006116 crossref_primary_10_1038_s41467_021_25960_2 crossref_primary_10_1093_bioadv_vbae011 crossref_primary_10_1038_s41569_021_00589_2 crossref_primary_10_1200_CCI_19_00095 crossref_primary_10_1186_s12864_018_4772_0 crossref_primary_10_3390_jpm12101750 crossref_primary_10_1093_bioadv_vbae019 crossref_primary_10_34133_research_0011 crossref_primary_10_1093_bib_bbad026 crossref_primary_10_1007_s11704_022_2011_y crossref_primary_10_1016_j_celrep_2020_107805 crossref_primary_10_1038_s41467_018_05112_9 crossref_primary_10_1073_pnas_2008890118 crossref_primary_10_3389_fcvm_2018_00167 crossref_primary_10_3389_fgene_2021_655536 crossref_primary_10_1126_sciimmunol_aal2192 crossref_primary_10_3390_genes11040377 crossref_primary_10_3390_e24070995 crossref_primary_10_1016_j_celrep_2021_110234 crossref_primary_10_1038_s41467_018_07582_3 crossref_primary_10_1038_s41568_023_00591_5 crossref_primary_10_1016_j_jaci_2022_08_010 crossref_primary_10_1186_s13059_017_1218_y crossref_primary_10_1016_j_immuni_2016_10_021 crossref_primary_10_1186_s12859_019_3243_1 crossref_primary_10_1038_ncomms9687 crossref_primary_10_1016_j_celrep_2018_08_080 crossref_primary_10_1287_ijoc_2020_1019 crossref_primary_10_1016_j_devcel_2019_10_003 crossref_primary_10_1038_s41592_021_01171_x crossref_primary_10_26508_lsa_202201701 crossref_primary_10_1016_j_csbj_2020_03_005 crossref_primary_10_1186_s12859_017_1994_0 crossref_primary_10_1016_j_celrep_2022_111639 crossref_primary_10_1126_sciimmunol_abm2508 crossref_primary_10_1038_s41467_023_36637_3 crossref_primary_10_1089_cmb_2022_0273 crossref_primary_10_3390_math13040673 crossref_primary_10_1186_s13059_015_0844_5 crossref_primary_10_1063_1_5024744 crossref_primary_10_1093_bib_bbad040 crossref_primary_10_1016_j_cels_2017_10_003 crossref_primary_10_1038_s41467_021_21246_9 crossref_primary_10_1186_s13059_022_02749_0 crossref_primary_10_3389_fonc_2021_796477 crossref_primary_10_1038_s41467_018_02892_y crossref_primary_10_1515_ijb_2020_0039 crossref_primary_10_1002_widm_1414 crossref_primary_10_1109_TCBB_2022_3227202 crossref_primary_10_1126_science_aad8361 crossref_primary_10_1038_s41592_018_0033_z crossref_primary_10_1002_ange_201709719 crossref_primary_10_1002_sim_9334 crossref_primary_10_3390_genes8120368 crossref_primary_10_1089_cmb_2019_0278 crossref_primary_10_1038_s44222_023_00132_7 crossref_primary_10_1016_j_molmet_2017_05_015 crossref_primary_10_1186_s13059_017_1171_9 crossref_primary_10_1007_s00439_020_02237_0 crossref_primary_10_1016_j_coisb_2017_08_003 crossref_primary_10_1186_s13619_021_00083_7 crossref_primary_10_1038_s41467_020_16905_2 crossref_primary_10_1038_nature23449 crossref_primary_10_1126_science_aad7038 crossref_primary_10_1038_s41587_019_0379_5 crossref_primary_10_1186_s13059_017_1382_0 crossref_primary_10_1016_j_isci_2022_105497 crossref_primary_10_1038_s42255_019_0102_3 crossref_primary_10_1038_s41568_022_00502_0 crossref_primary_10_1016_j_stem_2017_08_003 crossref_primary_10_1093_bib_bbaa190 crossref_primary_10_1186_s13059_021_02341_y crossref_primary_10_7717_peerj_10091 crossref_primary_10_1242_dev_172916 crossref_primary_10_1093_nar_gky698 crossref_primary_10_1186_s13619_020_00042_8 crossref_primary_10_1164_rccm_202008_3198OC crossref_primary_10_1093_bib_bbab039 crossref_primary_10_1371_journal_pcbi_1004575 crossref_primary_10_1109_ACCESS_2022_3202187 crossref_primary_10_1038_s41588_022_01014_1 crossref_primary_10_1038_ncomms15700 crossref_primary_10_1038_s43587_023_00373_6 crossref_primary_10_1158_0008_5472_CAN_20_1034 crossref_primary_10_1038_s41559_019_0946_7 crossref_primary_10_15252_embr_201540538 crossref_primary_10_1093_bib_bbac166 crossref_primary_10_1016_j_compbiomed_2024_108769 crossref_primary_10_1038_s41467_018_03405_7 crossref_primary_10_1016_j_cels_2018_04_008 crossref_primary_10_1016_j_ygeno_2021_01_007 crossref_primary_10_1186_s12859_023_05417_7 crossref_primary_10_1242_dev_123547 crossref_primary_10_1002_wsbm_1297 crossref_primary_10_1016_j_ygeno_2021_02_014 crossref_primary_10_1103_PhysRevE_107_044403 crossref_primary_10_1038_s41467_024_47884_3 crossref_primary_10_1213_ANE_0000000000002505 crossref_primary_10_1038_s41467_020_17900_3 crossref_primary_10_1016_j_mce_2018_01_013 crossref_primary_10_1093_bib_bbac398 crossref_primary_10_3389_fpls_2020_603302 crossref_primary_10_7554_eLife_22906 crossref_primary_10_1145_3641284 crossref_primary_10_1101_gr_201954_115 crossref_primary_10_1021_acsinfecdis_8b00369 crossref_primary_10_1038_nbt_3445 crossref_primary_10_1158_0008_5472_CAN_20_1037 crossref_primary_10_1186_s13059_018_1406_4 crossref_primary_10_3390_cancers11122025
Cites_doi	10.1038/nbt.2450 10.1093/bioinformatics/btm453 10.1186/gb-2010-11-10-r106 10.1089/scd.2007.0211 10.1016/j.fertnstert.2007.03.041 10.1038/nmeth.1315 10.1126/science.1245316 10.1038/nbt.2282 10.1038/nbt.2642 10.1093/bioinformatics/btp120 10.1016/j.celrep.2012.08.003 10.1016/j.copbio.2012.09.013 10.1371/journal.pone.0021208 10.1093/molehr/gah167 10.1038/nbt.2038 10.1038/nprot.2008.65 10.1038/nmeth.2645 10.1002/dvdy.23850 10.1126/science.1216379 10.1093/bioinformatics/bts714 10.1101/gr.110882.110 10.1093/bioinformatics/btr653 10.1016/j.cell.2012.08.023
ContentType	Journal Article
Copyright	Springer Nature America, Inc. 2014 COPYRIGHT 2014 Nature Publishing Group Copyright Nature Publishing Group Jul 2014
Copyright_xml	– notice: Springer Nature America, Inc. 2014 – notice: COPYRIGHT 2014 Nature Publishing Group – notice: Copyright Nature Publishing Group Jul 2014
DBID	AAYXX CITATION CGR CUY CVF ECM EIF NPM 3V. 7QL 7QO 7SS 7TK 7U9 7X2 7X7 7XB 88E 88I 8AO 8FD 8FE 8FG 8FH 8FI 8FJ 8FK ABJCF ABUWG AEUYN AFKRA ARAPS ATCPS AZQEC BBNVY BENPR BGLVJ BHPHI BKSAR C1K CCPQU D1I DWQXO FR3 FYUFA GHDGH GNUQQ H94 HCIFZ K9. KB. L6V LK8 M0K M0S M1P M2P M7N M7P M7S P5Z P62 P64 PATMY PCBAR PDBOC PHGZM PHGZT PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS PTHSS PYCSY Q9U RC3 7X8 5PM ADTOC UNPAY
DOI	10.1038/nmeth.2967
DatabaseName	CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed ProQuest Central (Corporate) Bacteriology Abstracts (Microbiology B) Biotechnology Research Abstracts Entomology Abstracts (Full archive) Neurosciences Abstracts Virology and AIDS Abstracts Agricultural Science Collection Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) Science Database (Alumni Edition) ProQuest Pharma Collection Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Natural Science Journals Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) Materials Science & Engineering Collection ProQuest Central (Alumni) ProQuest One Sustainability (subscription) ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection Agricultural & Environmental Science Collection ProQuest Central Essentials Biological Science Collection (subscription) ProQuest Central Technology Collection Natural Science Collection Earth, Atmospheric & Aquatic Science Collection Environmental Sciences and Pollution Management ProQuest One Community College ProQuest Materials Science Collection ProQuest Central Engineering Research Database Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student AIDS and Cancer Research Abstracts SciTech Premium ProQuest Health & Medical Complete (Alumni) Materials Science Database ProQuest Engineering Collection ProQuest Biological Science Collection Agricultural Science Database Health & Medical Collection (Alumni Edition) Medical Database Science Database Algology Mycology and Protozoology Abstracts (Microbiology C) Biological Science Database Engineering Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection Biotechnology and BioEngineering Abstracts Environmental Science Database Earth, Atmospheric & Aquatic Science Database Materials Science Collection ProQuest Central Premium ProQuest One Academic ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China Engineering Collection Environmental Science Collection ProQuest Central Basic Genetics Abstracts MEDLINE - Academic PubMed Central (Full Participant titles) Unpaywall for CDI: Periodical Content Unpaywall
DatabaseTitle	CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Agricultural Science Database ProQuest Central Student ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials SciTech Premium Collection ProQuest Central China Environmental Sciences and Pollution Management ProQuest One Applied & Life Sciences ProQuest One Sustainability Health Research Premium Collection Natural Science Collection Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) Engineering Collection Advanced Technologies & Aerospace Collection Engineering Database Virology and AIDS Abstracts ProQuest Science Journals (Alumni Edition) ProQuest Biological Science Collection ProQuest One Academic Eastern Edition Earth, Atmospheric & Aquatic Science Database Agricultural Science Collection ProQuest Hospital Collection ProQuest Technology Collection Health Research Premium Collection (Alumni) Biological Science Database Neurosciences Abstracts ProQuest Hospital Collection (Alumni) Biotechnology and BioEngineering Abstracts Environmental Science Collection Entomology Abstracts ProQuest Health & Medical Complete ProQuest One Academic UKI Edition Environmental Science Database Engineering Research Database ProQuest One Academic ProQuest One Academic (New) Technology Collection Technology Research Database ProQuest One Academic Middle East (New) Materials Science Collection ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing ProQuest Natural Science Collection ProQuest Pharma Collection ProQuest Central Earth, Atmospheric & Aquatic Science Collection ProQuest Health & Medical Research Collection Genetics Abstracts ProQuest Engineering Collection Biotechnology Research Abstracts Health and Medicine Complete (Alumni Edition) ProQuest Central Korea Bacteriology Abstracts (Microbiology B) Algology Mycology and Protozoology Abstracts (Microbiology C) Agricultural & Environmental Science Collection AIDS and Cancer Research Abstracts Materials Science Database ProQuest Materials Science Collection ProQuest Central Basic ProQuest Science Journals ProQuest SciTech Collection Advanced Technologies & Aerospace Database ProQuest Medical Library Materials Science & Engineering Collection ProQuest Central (Alumni) MEDLINE - Academic
DatabaseTitleList	MEDLINE MEDLINE - Academic Agricultural Science Database
Database_xml	– sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database – sequence: 3 dbid: UNPAY name: Unpaywall url: https://proxy.k.utb.cz/login?url=https://unpaywall.org/ sourceTypes: Open Access Repository – sequence: 4 dbid: 8FG name: ProQuest Technology Collection url: https://search.proquest.com/technologycollection1 sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Biology
EISSN	1548-7105
EndPage	742
ExternalDocumentID	oai:pubmedcentral.nih.gov:4112276 PMC4112276 3415797131 A373578973 24836921 10_1038_nmeth_2967
Genre	Research Support, Non-U.S. Gov't Journal Article Research Support, N.I.H., Extramural Feature
GrantInformation_xml	– fundername: NHLBI NIH HHS grantid: R01 HL097794 – fundername: NHLBI NIH HHS grantid: R01HL097794-03 – fundername: NHLBI NIH HHS grantid: U01 HL100402 – fundername: NIA NIH HHS grantid: K25 AG037596 – fundername: NIA NIH HHS grantid: K25AG037596 – fundername: NIDDK NIH HHS grantid: R01 DK050234 – fundername: NIDDK NIH HHS grantid: R01DK050234-15A1
GroupedDBID	--- -~X 0R~ 123 29M 39C 3V. 4.4 53G 5BI 7X2 7X7 7XC 88E 88I 8AO 8CJ 8FE 8FG 8FH 8FI 8FJ 8R4 8R5 AAEEF AAHBH AARCD AAYZH AAZLF ABAWZ ABDBF ABJCF ABJNI ABLJU ABUWG ACBWK ACGFS ACGOD ACIWK ACPRK ACUHS ADBBV AENEX AEUYN AFANA AFBBN AFKRA AFRAH AFSHS AGAYW AHBCP AHMBA AHSBF AIBTJ ALFFA ALIPV ALMA_UNASSIGNED_HOLDINGS ARAPS ARMCB ASPBG ATCPS AVWKF AXYYD AZFZN AZQEC BBNVY BENPR BGLVJ BHPHI BKKNO BKSAR BPHCQ BVXVI CCPQU CS3 D1I D1J D1K DB5 DU5 DWQXO EBS EE. EJD EMOBN ESX F5P FEDTE FSGXE FYUFA FZEXT GNUQQ HCIFZ HMCUK HVGLF HZ~ IAO IHR INH INR ITC K6- KB. L6V LK5 LK8 M0K M1P M2P M7P M7R M7S NNMJJ O9- ODYON P2P P62 PATMY PCBAR PDBOC PQQKQ PROAC PSQYO PTHSS PYCSY Q2X RNS RNT RNTTT SHXYY SIXXV SJN SNYQT SOJ SV3 TAOOD TBHMF TDRGL TSG TUS UKHRP ~8M AAYXX ATHPR CITATION PHGZM PHGZT PJZUB PPXIY PQGLB PUEGO CGR CUY CVF ECM EIF NFIDA NPM 7QL 7QO 7SS 7TK 7U9 7XB 8FD 8FK C1K FR3 H94 K9. M7N P64 PKEHL PQEST PQUKI PRINS Q9U RC3 7X8 5PM ADTOC AFFHD AGSTI UNPAY
ID	FETCH-LOGICAL-c645t-3dc6fb3399000af33fb560f4439da010291fbdb70df8144a5648d50b8d5602ac3
IEDL.DBID	BENPR
ISSN	1548-7091 1548-7105
IngestDate	Wed Oct 29 12:12:36 EDT 2025 Tue Sep 30 15:41:45 EDT 2025 Wed Oct 01 10:48:49 EDT 2025 Mon Oct 06 17:04:55 EDT 2025 Mon Oct 20 22:06:22 EDT 2025 Mon Oct 20 16:49:23 EDT 2025 Thu Apr 03 07:27:09 EDT 2025 Thu Apr 24 22:58:03 EDT 2025 Wed Oct 01 01:14:50 EDT 2025 Fri Feb 21 02:37:46 EST 2025
IsDoiOpenAccess	true
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Issue	7
Language	English
License	Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c645t-3dc6fb3399000af33fb560f4439da010291fbdb70df8144a5648d50b8d5602ac3
Notes	SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23
OpenAccessLink	https://proxy.k.utb.cz/login?url=http://doi.org/10.1038/nmeth.2967
PMID	24836921
PQID	1557651678
PQPubID	28015
PageCount	3
ParticipantIDs	unpaywall_primary_10_1038_nmeth_2967 pubmedcentral_primary_oai_pubmedcentral_nih_gov_4112276 proquest_miscellaneous_1541382418 proquest_journals_1557651678 gale_infotracmisc_A373578973 gale_infotracacademiconefile_A373578973 pubmed_primary_24836921 crossref_primary_10_1038_nmeth_2967 crossref_citationtrail_10_1038_nmeth_2967 springer_journals_10_1038_nmeth_2967
ProviderPackageCode	CITATION AAYXX
PublicationCentury	2000
PublicationDate	2014-07-01
PublicationDateYYYYMMDD	2014-07-01
PublicationDate_xml	– month: 07 year: 2014 text: 2014-07-01 day: 01
PublicationDecade	2010
PublicationPlace	New York
PublicationPlace_xml	– name: New York – name: United States
PublicationSubtitle	Techniques for life scientists and chemists
PublicationTitle	Nature methods
PublicationTitleAbbrev	Nat Methods
PublicationTitleAlternate	Nat Methods
PublicationYear	2014
Publisher	Nature Publishing Group US Nature Publishing Group
Publisher_xml	– name: Nature Publishing Group US – name: Nature Publishing Group
References	IslamSGenome Res.201121116011671:CAS:528:DC%2BC3MXovVKkurg%3D10.1101/gr.110882.110 MunskyBNeuertGvan OudenaardenAScience20123361831871:CAS:528:DC%2BC38Xlt1ehsb8%3D10.1126/science.1216379 AndängMMolinerADoegeCAIbanezCFErnforsPNat. Protoc.200831013101710.1038/nprot.2008.65 TangFPLoS ONE20116e212081:CAS:528:DC%2BC3MXotF2ms7s%3D10.1371/journal.pone.0021208 GrünBScharlTLeischFBioinformatics20122822222810.1093/bioinformatics/btr653 RamsköldDNat. Biotechnol.20123077778210.1038/nbt.2282 BrenneckePNat. Methods201310109310951:CAS:528:DC%2BC3sXhsVyqtb3L10.1038/nmeth.2645 DengQRamskoldDReiniusBSandbergRScience20143431931961:CAS:528:DC%2BC2cXktVykug%3D%3D10.1126/science.1245316 PanHAFertil. Steril.200889132413271:CAS:528:DC%2BD1cXht12qsLjP10.1016/j.fertnstert.2007.03.041 TrapnellCPachterLSalzbergSLBioinformatics200925110511111:CAS:528:DC%2BD1MXltFWisrk%3D10.1093/bioinformatics/btp120 TrapnellCNat. Biotechnol.20133146531:CAS:528:DC%2BC38Xhsl2lu7jL10.1038/nbt.2450 MolinerAEnforsPIbanezCFAndangMStem Cells Dev.2008172332431:CAS:528:DC%2BD1cXltlSmsrk%3D10.1089/scd.2007.0211 BrouiletteSDev. Dyn.2012241158415901:CAS:528:DC%2BC38Xhtl2ntr3N10.1002/dvdy.23850 McDavidABioinformatics2013294614671:CAS:528:DC%2BC3sXis1OjsLs%3D10.1093/bioinformatics/bts714 DalerbaPNat. Biotechnol.201129112011271:CAS:528:DC%2BC3MXhsVKjsbfI10.1038/nbt.2038 BuganimYCell2012150120912221:CAS:528:DC%2BC38XhtlKrs7vM10.1016/j.cell.2012.08.023 TangFNat. Methods200963773821:CAS:528:DC%2BD1MXktVKgu78%3D10.1038/nmeth.1315 AndersSHuberWGenome Biol.201011R1061:CAS:528:DC%2BC3cXhsVahs7bI10.1186/gb-2010-11-10-r106 WillsQFNat. Biotechnol.2013317487521:CAS:528:DC%2BC3sXhtFCisr7E10.1038/nbt.2642 HashimshonyTWagnerFSherNYanaiICell Reports201226666731:CAS:528:DC%2BC38XhsFSmsL3J10.1016/j.celrep.2012.08.003 RobinsonMDSmythGKBioinformatics200723288128871:CAS:528:DC%2BD2sXhtlaqsL%2FK10.1093/bioinformatics/btm453 CauffmanGMol. Hum. Reprod.2005114054111:CAS:528:DC%2BD2MXmvFegsLc%3D10.1093/molehr/gah167 TischlerJSuraniMACurr. Opin. Biotechnol.20132469781:CAS:528:DC%2BC38XhsFCnsLvN10.1016/j.copbio.2012.09.013 F Tang (BFnmeth2967_CR1) 2009; 6 C Trapnell (BFnmeth2967_CR21) 2009; 25 Y Buganim (BFnmeth2967_CR8) 2012; 150 P Brennecke (BFnmeth2967_CR10) 2013; 10 QF Wills (BFnmeth2967_CR11) 2013; 31 MD Robinson (BFnmeth2967_CR16) 2007; 23 S Islam (BFnmeth2967_CR2) 2011; 21 D Ramsköld (BFnmeth2967_CR4) 2012; 30 T Hashimshony (BFnmeth2967_CR3) 2012; 2 P Dalerba (BFnmeth2967_CR5) 2011; 29 C Trapnell (BFnmeth2967_CR14) 2013; 31 F Tang (BFnmeth2967_CR6) 2011; 6 HA Pan (BFnmeth2967_CR20) 2008; 89 G Cauffman (BFnmeth2967_CR19) 2005; 11 M Andäng (BFnmeth2967_CR23) 2008; 3 S Brouilette (BFnmeth2967_CR7) 2012; 241 A Moliner (BFnmeth2967_CR17) 2008; 17 J Tischler (BFnmeth2967_CR18) 2013; 24 Q Deng (BFnmeth2967_CR12) 2014; 343 S Anders (BFnmeth2967_CR13) 2010; 11 B Grün (BFnmeth2967_CR22) 2012; 28 B Munsky (BFnmeth2967_CR9) 2012; 336 A McDavid (BFnmeth2967_CR15) 2013; 29
References_xml	– reference: BrenneckePNat. Methods201310109310951:CAS:528:DC%2BC3sXhsVyqtb3L10.1038/nmeth.2645 – reference: McDavidABioinformatics2013294614671:CAS:528:DC%2BC3sXis1OjsLs%3D10.1093/bioinformatics/bts714 – reference: AndängMMolinerADoegeCAIbanezCFErnforsPNat. Protoc.200831013101710.1038/nprot.2008.65 – reference: TangFPLoS ONE20116e212081:CAS:528:DC%2BC3MXotF2ms7s%3D10.1371/journal.pone.0021208 – reference: IslamSGenome Res.201121116011671:CAS:528:DC%2BC3MXovVKkurg%3D10.1101/gr.110882.110 – reference: CauffmanGMol. Hum. Reprod.2005114054111:CAS:528:DC%2BD2MXmvFegsLc%3D10.1093/molehr/gah167 – reference: MolinerAEnforsPIbanezCFAndangMStem Cells Dev.2008172332431:CAS:528:DC%2BD1cXltlSmsrk%3D10.1089/scd.2007.0211 – reference: DengQRamskoldDReiniusBSandbergRScience20143431931961:CAS:528:DC%2BC2cXktVykug%3D%3D10.1126/science.1245316 – reference: HashimshonyTWagnerFSherNYanaiICell Reports201226666731:CAS:528:DC%2BC38XhsFSmsL3J10.1016/j.celrep.2012.08.003 – reference: RamsköldDNat. Biotechnol.20123077778210.1038/nbt.2282 – reference: TrapnellCNat. Biotechnol.20133146531:CAS:528:DC%2BC38Xhsl2lu7jL10.1038/nbt.2450 – reference: WillsQFNat. Biotechnol.2013317487521:CAS:528:DC%2BC3sXhtFCisr7E10.1038/nbt.2642 – reference: TrapnellCPachterLSalzbergSLBioinformatics200925110511111:CAS:528:DC%2BD1MXltFWisrk%3D10.1093/bioinformatics/btp120 – reference: RobinsonMDSmythGKBioinformatics200723288128871:CAS:528:DC%2BD2sXhtlaqsL%2FK10.1093/bioinformatics/btm453 – reference: BrouiletteSDev. Dyn.2012241158415901:CAS:528:DC%2BC38Xhtl2ntr3N10.1002/dvdy.23850 – reference: TangFNat. Methods200963773821:CAS:528:DC%2BD1MXktVKgu78%3D10.1038/nmeth.1315 – reference: AndersSHuberWGenome Biol.201011R1061:CAS:528:DC%2BC3cXhsVahs7bI10.1186/gb-2010-11-10-r106 – reference: TischlerJSuraniMACurr. Opin. Biotechnol.20132469781:CAS:528:DC%2BC38XhsFCnsLvN10.1016/j.copbio.2012.09.013 – reference: PanHAFertil. Steril.200889132413271:CAS:528:DC%2BD1cXht12qsLjP10.1016/j.fertnstert.2007.03.041 – reference: DalerbaPNat. Biotechnol.201129112011271:CAS:528:DC%2BC3MXhsVKjsbfI10.1038/nbt.2038 – reference: BuganimYCell2012150120912221:CAS:528:DC%2BC38XhtlKrs7vM10.1016/j.cell.2012.08.023 – reference: GrünBScharlTLeischFBioinformatics20122822222810.1093/bioinformatics/btr653 – reference: MunskyBNeuertGvan OudenaardenAScience20123361831871:CAS:528:DC%2BC38Xlt1ehsb8%3D10.1126/science.1216379 – volume: 31 start-page: 46 year: 2013 ident: BFnmeth2967_CR14 publication-title: Nat. Biotechnol. doi: 10.1038/nbt.2450 – volume: 23 start-page: 2881 year: 2007 ident: BFnmeth2967_CR16 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btm453 – volume: 11 start-page: R106 year: 2010 ident: BFnmeth2967_CR13 publication-title: Genome Biol. doi: 10.1186/gb-2010-11-10-r106 – volume: 17 start-page: 233 year: 2008 ident: BFnmeth2967_CR17 publication-title: Stem Cells Dev. doi: 10.1089/scd.2007.0211 – volume: 89 start-page: 1324 year: 2008 ident: BFnmeth2967_CR20 publication-title: Fertil. Steril. doi: 10.1016/j.fertnstert.2007.03.041 – volume: 6 start-page: 377 year: 2009 ident: BFnmeth2967_CR1 publication-title: Nat. Methods doi: 10.1038/nmeth.1315 – volume: 343 start-page: 193 year: 2014 ident: BFnmeth2967_CR12 publication-title: Science doi: 10.1126/science.1245316 – volume: 30 start-page: 777 year: 2012 ident: BFnmeth2967_CR4 publication-title: Nat. Biotechnol. doi: 10.1038/nbt.2282 – volume: 31 start-page: 748 year: 2013 ident: BFnmeth2967_CR11 publication-title: Nat. Biotechnol. doi: 10.1038/nbt.2642 – volume: 25 start-page: 1105 year: 2009 ident: BFnmeth2967_CR21 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btp120 – volume: 2 start-page: 666 year: 2012 ident: BFnmeth2967_CR3 publication-title: Cell Reports doi: 10.1016/j.celrep.2012.08.003 – volume: 24 start-page: 69 year: 2013 ident: BFnmeth2967_CR18 publication-title: Curr. Opin. Biotechnol. doi: 10.1016/j.copbio.2012.09.013 – volume: 6 start-page: e21208 year: 2011 ident: BFnmeth2967_CR6 publication-title: PLoS ONE doi: 10.1371/journal.pone.0021208 – volume: 11 start-page: 405 year: 2005 ident: BFnmeth2967_CR19 publication-title: Mol. Hum. Reprod. doi: 10.1093/molehr/gah167 – volume: 29 start-page: 1120 year: 2011 ident: BFnmeth2967_CR5 publication-title: Nat. Biotechnol. doi: 10.1038/nbt.2038 – volume: 3 start-page: 1013 year: 2008 ident: BFnmeth2967_CR23 publication-title: Nat. Protoc. doi: 10.1038/nprot.2008.65 – volume: 10 start-page: 1093 year: 2013 ident: BFnmeth2967_CR10 publication-title: Nat. Methods doi: 10.1038/nmeth.2645 – volume: 241 start-page: 1584 year: 2012 ident: BFnmeth2967_CR7 publication-title: Dev. Dyn. doi: 10.1002/dvdy.23850 – volume: 336 start-page: 183 year: 2012 ident: BFnmeth2967_CR9 publication-title: Science doi: 10.1126/science.1216379 – volume: 29 start-page: 461 year: 2013 ident: BFnmeth2967_CR15 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bts714 – volume: 21 start-page: 1160 year: 2011 ident: BFnmeth2967_CR2 publication-title: Genome Res. doi: 10.1101/gr.110882.110 – volume: 28 start-page: 222 year: 2012 ident: BFnmeth2967_CR22 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btr653 – volume: 150 start-page: 1209 year: 2012 ident: BFnmeth2967_CR8 publication-title: Cell doi: 10.1016/j.cell.2012.08.023
SSID	ssj0033425
Score	2.6437287
Snippet	A method to model expression variability in single-cell RNA-seq measurements and thus to improve subsequent data analysis. Single-cell data provide a means to... Single-cell data provide a means to dissect the composition of complex tissues and specialized cellular environments. However, the analysis of such... Single-cell data provides means to dissect the composition of complex tissues and specialized cellular environments. However, the analysis of such measurements...
SourceID	unpaywall pubmedcentral proquest gale pubmed crossref springer
SourceType	Open Access Repository Aggregation Database Index Database Enrichment Source Publisher
StartPage	740
SubjectTerms	38/91 631/114/2415 631/1647/2217/2218 631/208/212/2019 Algorithms Analysis Bayes Theorem Bayesian analysis Bayesian statistical decision theory Bioinformatics Biological Microscopy Biological Techniques Biomedical Engineering/Biotechnology brief-communication Cell differentiation Cellular biology Gene expression Gene Expression Profiling - methods Life Sciences Oligonucleotide Array Sequence Analysis Physiological aspects Protein expression Proteomics Ribonucleic acid RNA Sequence Analysis, RNA - methods Single-Cell Analysis - methods Subpopulations
SummonAdditionalLinks	– databaseName: Unpaywall dbid: UNPAY link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1Lb9QwEB6VrRDlwLNAoKAgVkIcvCSxYzvHBVFVSFQcWKmcIj8FapStSlaw_fUdbx5sSkHcIvlz5Ngz9hd7_A3AVCVGeMdSYvHfgjDKNdHSSmKZyHziEi1suI386ZgfLdjHk_xkB_r8hKPjeyrf1iGP8iwruLgBuzxHuj2B3cXx5_nXjQ4qk0QkRTo8I1noJUhHlUeLztWpd2vtuRoXORyO3oZbq_pMrX-qqtpafw7v_r7F04adnM5WjZ6Ziz9FHf_-affgTsc-43lrLvdhx9UP4Gabj3L9EObv1NqFW5VxLzUeN8s47CZUjoQt_rjPp4LzQhW7X10ULeI7bZN9WBx--PL-iHQ5FojhLG8ItYZ7TZGm4NyoPKVeIwfyDHmKVUFvrki9tlok1kv891I5Z9LmCY4nwjJl6COY1MvaPYGYuVzTzCFFcJKlVqnECyXQ6anJElqwCN70g1CaToA85MGoys1BOJXlpkvK0CURvBqwZ63sxrWo12Esy-CL-CajuisF2J6galXOqQhiPoWgERyMkOhDZlzcW0PZ-fCPEpmW4HmKq3kEL4fiUDPEpdVuuQoYFkQcWYqYx63xDO3NmKS8yNIIxMisBkBQ9h6X1N-_bRS-GbLgTPAIpr0BbjXrmm6YDsb5j956-n-wZ7CHpJC1IckHMGnOV-45Eq9Gv-hc7xJpWiuF priority: 102 providerName: Unpaywall
Title	Bayesian approach to single-cell differential expression analysis
URI	https://link.springer.com/article/10.1038/nmeth.2967 https://www.ncbi.nlm.nih.gov/pubmed/24836921 https://www.proquest.com/docview/1557651678 https://www.proquest.com/docview/1541382418 https://pubmed.ncbi.nlm.nih.gov/PMC4112276 http://doi.org/10.1038/nmeth.2967
UnpaywallVersion	submittedVersion
Volume	11
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVEBS databaseName: EBSCOhost Academic Search Ultimate customDbUrl: https://search.ebscohost.com/login.aspx?authtype=ip,shib&custid=s3936755&profile=ehost&defaultdb=asn eissn: 1548-7105 dateEnd: 20151130 omitProxy: true ssIdentifier: ssj0033425 issn: 1548-7105 databaseCode: ABDBF dateStart: 20041001 isFulltext: true titleUrlDefault: https://search.ebscohost.com/direct.asp?db=asn providerName: EBSCOhost – providerCode: PRVPQU databaseName: Health & Medical Collection customDbUrl: eissn: 1548-7105 dateEnd: 20171231 omitProxy: true ssIdentifier: ssj0033425 issn: 1548-7105 databaseCode: 7X7 dateStart: 20041001 isFulltext: true titleUrlDefault: https://search.proquest.com/healthcomplete providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: http://www.proquest.com/pqcentral?accountid=15518 eissn: 1548-7105 dateEnd: 20171231 omitProxy: true ssIdentifier: ssj0033425 issn: 1548-7105 databaseCode: BENPR dateStart: 20041001 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Technology Collection customDbUrl: eissn: 1548-7105 dateEnd: 20241102 omitProxy: true ssIdentifier: ssj0033425 issn: 1548-7105 databaseCode: 8FG dateStart: 20041001 isFulltext: true titleUrlDefault: https://search.proquest.com/technologycollection1 providerName: ProQuest
link	http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3db9MwED9trRDjAfG9wKiCqIR48JbETpw8IJTCyoRENSEqlafIiR2BFKUFWkH_e-6SOGunaS_tg6-Vc76v2OffD2CsvEKWRvhM47sFEzzKWR7rmGkhg9IzXi413Ub-Mosu5uLzIlwcwMzehaG2ShsTm0CtlwXtkZ9h3pNR6GNsfb_6xYg1ik5XLYWG6qgV9LsGYuwQhgEhYw1gODmfXX61sZlz0dCwUp3OJKZKC1jK47OaKJtPg6RhnL9KUdcD9U6mut5F2R-l3oO7m3qltn9VVe1kq-kDuN-VmW7a2sVDODD1I7jTEk9uH0M6UVtD1yddiynurpcubRtUhtFevmuJUzAAVK7517XLonwHYvIE5tPzbx8uWEemwIpIhGvGdRGVOcd6BIOgKjkvcyx2SoEFiVYELJf4Za5z6ekyxpcsFUYi1qGHC4digSr4UxjUy9ocgytMmPPAYC1gYuFrpbxSKonezYvA44lw4K3VX1Z0SONEeFFlzYk3j7NG1xnp2oHXveyqxde4UeoNLUNGTof_VKju7gDOh-CrspRLQu1JJHfgZE8SnaXYH7YLmXXO-ie7Mi0HXvXD9EtqQKvNckMygtAahY8yz9p17-cbiJhHSeA7IPcsohcgCO_9kfrnjwbKW2C5G8jIgbG1nZ1p3aCGcW9Xt2jr-e0P-QKOsOoTbc_xCQzWvzfmJVZW63wEh3Ih8TOefhrBMJ18nExHnQvh93x2mX7_D_VPKSY
linkProvider	ProQuest
linkToHtml	http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3fb9MwED6NTWjjAfFzBAYEUYR4MEtsJ04eJtTBpo5tFUKbtLfgxI5AitLCWo3-c_xt3KVx1k7T3vbsS-Scz3fn-O77AHo6KFRpZcgMni2YFHHO8sQkzEjFy8AGuTLUjXw8jAen8utZdLYC_1wvDJVVOp_YOGozKugf-TbGPRVHIfrWT-PfjFij6HbVUWjollrB7DQQY21jx6GdXeAR7nzn4Auu9zvO9_dOPg9YyzLAilhGEyZMEZe5wECN3kGXQpQ5ZgGlxEhtNCGupWGZm1wFpkzw9KGjWCYmCvCLUIzrQuB778CaFDLFw9_a7t7w23cXC4SQDe0rnQuYwtDsAFJFsl0TRfRHnjYM95ch8WpgWIiMV6s2u6vbe7A-rcd6dqGraiE67j-A-21a6_fndvgQVmz9CO7OiS5nj6G_q2eW2jV9h2HuT0Y-_aaoLKO7A98RtaDDqXz7ty3PRfkWNOUJnN6KWp_Caj2q7TPwpY1ywS3mHjaRodE6KJVW6E1EwQORSg8-OP1lRYtsTgQbVdbcsIska3Sdka49eNvJjud4HtdKvadlyGiT45sK3fYq4HwILivrC0UoQakSHmwtSeLmLJaH3UJmrXM4zy5N2YM33TA9SQVvtR1NSUYSOqQMUWZzvu7dfLlMRJzy0AO1ZBGdAEGGL4_Uv3420OES02uuYg96znYWpnWNGnqdXd2grec3f-RrWB-cHB9lRwfDwxewgRmnnNc7b8Hq5M_UvsSsbpK_areODz9ue7f-B832YGk
linkToPdf	http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwEB6VIigcEK9CoEAQiyoOZhPbiZMDQgtl1VKoOFBpb8GJbYEUZRe6q7J_jV_HTF7drareevbEssfzjMffAAx0UChnZcgM5hZMijhneWISZqTiLrBBrgy9Rv56FO8fy8-TaLIB_7q3MFRW2dnE2lCbaUH_yIfo91QchWhbh64ti_i2N34_-82ogxTdtHbtNBoRObTLU0zfTt4d7OFZv-Z8_On7x33WdhhgRSyjOROmiF0u0EmjZdBOCJdjBOAkemmjCW0tDV1uchUYl2DmoaNYJiYKcDdIxnUhcN5rcF3hDFROqCZ9sieErBu-UkbAFDrlDhpVJMOKmkO_5Wnd2_7MGZ53CSs-8Xy9Zn9pexu2FtVML091Wa74xfFduNMGtP6okcB7sGGr-3CjaXG5fACjD3pp6aGm36GX-_OpTz8oSsvo1sDvWrSgqSl9-7ctzEX6Fi7lIRxfCVO3YbOaVvYx-NJGueAWow6byNBoHTilFdoRUfBApNKDNx3_sqLFNKfWGmVW362LJKt5nRGvPXjV084aJI8LqXbpGDJSb5yp0O0rBVwPAWVlI6EIHyhVwoOdNUpUy2J9uDvIrDULJ9mZEHvwsh-mL6nUrbLTBdFIwoWUIdI8as69Xy-XiYhTHnqg1iSiJyCw8PWR6tfPGjRcYmDNVezBoJOdlWVdwIZBL1eXcOvJ5Zt8ATdRR7MvB0eHT-EWhpqyKXTegc35n4V9huHcPH9e640PP65aUf8DKaBeAw
linkToUnpaywall	http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1Lb9QwEB6VrRDlwLNAoKAgVkIcvCSxYzvHBVFVSFQcWKmcIj8FapStSlaw_fUdbx5sSkHcIvlz5Ngz9hd7_A3AVCVGeMdSYvHfgjDKNdHSSmKZyHziEi1suI386ZgfLdjHk_xkB_r8hKPjeyrf1iGP8iwruLgBuzxHuj2B3cXx5_nXjQ4qk0QkRTo8I1noJUhHlUeLztWpd2vtuRoXORyO3oZbq_pMrX-qqtpafw7v_r7F04adnM5WjZ6Ziz9FHf_-affgTsc-43lrLvdhx9UP4Gabj3L9EObv1NqFW5VxLzUeN8s47CZUjoQt_rjPp4LzQhW7X10ULeI7bZN9WBx--PL-iHQ5FojhLG8ItYZ7TZGm4NyoPKVeIwfyDHmKVUFvrki9tlok1kv891I5Z9LmCY4nwjJl6COY1MvaPYGYuVzTzCFFcJKlVqnECyXQ6anJElqwCN70g1CaToA85MGoys1BOJXlpkvK0CURvBqwZ63sxrWo12Esy-CL-CajuisF2J6galXOqQhiPoWgERyMkOhDZlzcW0PZ-fCPEpmW4HmKq3kEL4fiUDPEpdVuuQoYFkQcWYqYx63xDO3NmKS8yNIIxMisBkBQ9h6X1N-_bRS-GbLgTPAIpr0BbjXrmm6YDsb5j956-n-wZ7CHpJC1IckHMGnOV-45Eq9Gv-hc7xJpWiuF
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Bayesian+approach+to+single-cell+differential+expression+analysis&rft.jtitle=Nature+methods&rft.au=Kharchenko%2C+Peter+V&rft.au=Silberstein%2C+Lev&rft.au=Scadden%2C+David+T&rft.date=2014-07-01&rft.pub=Nature+Publishing+Group&rft.issn=1548-7091&rft.volume=11&rft.issue=7&rft.spage=740&rft_id=info:doi/10.1038%2FNMETH.2967&rft.externalDocID=A373578973
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1548-7091&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1548-7091&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1548-7091&client=summon