Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling

Single-cell RNA sequencing has enabled the decomposition of complex tissues into functionally distinct cell types. Often, investigators wish to assign cells to cell types through unsupervised clustering followed by manual annotation or via 'mapping' to existing data. However, manual interp...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Nature methods Jg. 16; H. 10; S. 1007 - 1015
Hauptverfasser: Zhang, Allen W, O'Flanagan, Ciara, Chavez, Elizabeth A, Lim, Jamie L P, Ceglia, Nicholas, McPherson, Andrew, Wiens, Matt, Walters, Pascale, Chan, Tim, Hewitson, Brittany, Lai, Daniel, Mottok, Anja, Sarkozy, Clementine, Chong, Lauren, Aoki, Tomohiro, Wang, Xuehai, Weng, Andrew P, McAlpine, Jessica N, Aparicio, Samuel, Steidl, Christian, Campbell, Kieran R, Shah, Sohrab P
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States Nature Publishing Group 01.10.2019
Schlagworte:
ISSN:1548-7091, 1548-7105, 1548-7105
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Abstract Single-cell RNA sequencing has enabled the decomposition of complex tissues into functionally distinct cell types. Often, investigators wish to assign cells to cell types through unsupervised clustering followed by manual annotation or via 'mapping' to existing data. However, manual interpretation scales poorly to large datasets, mapping approaches require purified or pre-annotated data and both are prone to batch effects. To overcome these issues, we present CellAssign, a probabilistic model that leverages prior knowledge of cell-type marker genes to annotate single-cell RNA sequencing data into predefined or de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while controlling for batch and sample effects. We demonstrate the advantages of CellAssign through extensive simulations and analysis of tumor microenvironment composition in high-grade serous ovarian cancer and follicular lymphoma.
AbstractList Single-cell RNA sequencing has enabled the decomposition of complex tissues into functionally distinct cell types. Often, investigators wish to assign cells to cell types through unsupervised clustering followed by manual annotation or via 'mapping' to existing data. However, manual interpretation scales poorly to large datasets, mapping approaches require purified or pre-annotated data and both are prone to batch effects. To overcome these issues, we present CellAssign, a probabilistic model that leverages prior knowledge of cell-type marker genes to annotate single-cell RNA sequencing data into predefined or de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while controlling for batch and sample effects. We demonstrate the advantages of CellAssign through extensive simulations and analysis of tumor microenvironment composition in high-grade serous ovarian cancer and follicular lymphoma.
Single-cell RNA sequencing has enabled the decomposition of complex tissues into functionally distinct cell types. Often, investigators wish to assign cells to cell types through unsupervised clustering followed by manual annotation or via 'mapping' to existing data. However, manual interpretation scales poorly to large datasets, mapping approaches require purified or pre-annotated data and both are prone to batch effects. To overcome these issues, we present CellAssign, a probabilistic model that leverages prior knowledge of cell-type marker genes to annotate single-cell RNA sequencing data into predefined or de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while controlling for batch and sample effects. We demonstrate the advantages of CellAssign through extensive simulations and analysis of tumor microenvironment composition in high-grade serous ovarian cancer and follicular lymphoma.Single-cell RNA sequencing has enabled the decomposition of complex tissues into functionally distinct cell types. Often, investigators wish to assign cells to cell types through unsupervised clustering followed by manual annotation or via 'mapping' to existing data. However, manual interpretation scales poorly to large datasets, mapping approaches require purified or pre-annotated data and both are prone to batch effects. To overcome these issues, we present CellAssign, a probabilistic model that leverages prior knowledge of cell-type marker genes to annotate single-cell RNA sequencing data into predefined or de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while controlling for batch and sample effects. We demonstrate the advantages of CellAssign through extensive simulations and analysis of tumor microenvironment composition in high-grade serous ovarian cancer and follicular lymphoma.
Author McPherson, Andrew
Mottok, Anja
Wiens, Matt
Chan, Tim
Walters, Pascale
Aoki, Tomohiro
Lim, Jamie L P
Steidl, Christian
Campbell, Kieran R
Shah, Sohrab P
Chavez, Elizabeth A
Hewitson, Brittany
Weng, Andrew P
Sarkozy, Clementine
Ceglia, Nicholas
O'Flanagan, Ciara
Aparicio, Samuel
Wang, Xuehai
McAlpine, Jessica N
Chong, Lauren
Zhang, Allen W
Lai, Daniel
Author_xml – sequence: 1
  givenname: Allen W
  orcidid: 0000-0002-7606-089X
  surname: Zhang
  fullname: Zhang, Allen W
  organization: BC Children's Hospital Research, Vancouver, British Columbia, Canada
– sequence: 2
  givenname: Ciara
  surname: O'Flanagan
  fullname: O'Flanagan, Ciara
  organization: Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada
– sequence: 3
  givenname: Elizabeth A
  surname: Chavez
  fullname: Chavez, Elizabeth A
  organization: Centre for Lymphoid Cancer, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada
– sequence: 4
  givenname: Jamie L P
  surname: Lim
  fullname: Lim, Jamie L P
  organization: Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
– sequence: 5
  givenname: Nicholas
  surname: Ceglia
  fullname: Ceglia, Nicholas
  organization: Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
– sequence: 6
  givenname: Andrew
  surname: McPherson
  fullname: McPherson, Andrew
  organization: Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada
– sequence: 7
  givenname: Matt
  surname: Wiens
  fullname: Wiens, Matt
  organization: Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada
– sequence: 8
  givenname: Pascale
  surname: Walters
  fullname: Walters, Pascale
  organization: Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada
– sequence: 9
  givenname: Tim
  surname: Chan
  fullname: Chan, Tim
  organization: Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada
– sequence: 10
  givenname: Brittany
  surname: Hewitson
  fullname: Hewitson, Brittany
  organization: Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada
– sequence: 11
  givenname: Daniel
  orcidid: 0000-0001-9203-6323
  surname: Lai
  fullname: Lai, Daniel
  organization: Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada
– sequence: 12
  givenname: Anja
  surname: Mottok
  fullname: Mottok, Anja
  organization: Institute of Human Genetics, Ulm University and Ulm University Medical Center, Ulm, Germany
– sequence: 13
  givenname: Clementine
  surname: Sarkozy
  fullname: Sarkozy, Clementine
  organization: Centre for Lymphoid Cancer, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada
– sequence: 14
  givenname: Lauren
  surname: Chong
  fullname: Chong, Lauren
  organization: Centre for Lymphoid Cancer, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada
– sequence: 15
  givenname: Tomohiro
  orcidid: 0000-0001-6782-8361
  surname: Aoki
  fullname: Aoki, Tomohiro
  organization: Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
– sequence: 16
  givenname: Xuehai
  surname: Wang
  fullname: Wang, Xuehai
  organization: Terry Fox Laboratory, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada
– sequence: 17
  givenname: Andrew P
  surname: Weng
  fullname: Weng, Andrew P
  organization: Terry Fox Laboratory, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada
– sequence: 18
  givenname: Jessica N
  surname: McAlpine
  fullname: McAlpine, Jessica N
  organization: Department of Obstetrics & Gynaecology, University of British Columbia, Vancouver, British Columbia, Canada
– sequence: 19
  givenname: Samuel
  orcidid: 0000-0002-0487-9599
  surname: Aparicio
  fullname: Aparicio, Samuel
  organization: Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
– sequence: 20
  givenname: Christian
  surname: Steidl
  fullname: Steidl, Christian
  organization: Centre for Lymphoid Cancer, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada
– sequence: 21
  givenname: Kieran R
  orcidid: 0000-0003-1981-5763
  surname: Campbell
  fullname: Campbell, Kieran R
  email: kieran.campbell@stat.ubc.ca, kieran.campbell@stat.ubc.ca, kieran.campbell@stat.ubc.ca
  organization: UBC Data Science Institute, University of British Columbia, Vancouver, British Columbia, Canada. kieran.campbell@stat.ubc.ca
– sequence: 22
  givenname: Sohrab P
  orcidid: 0000-0001-6402-523X
  surname: Shah
  fullname: Shah, Sohrab P
  email: shahs3@mskcc.org, shahs3@mskcc.org, shahs3@mskcc.org
  organization: Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada. shahs3@mskcc.org
BackLink https://www.ncbi.nlm.nih.gov/pubmed/31501550$$D View this record in MEDLINE/PubMed
BookMark eNpdkE1LAzEQhoNU7If-AC-y4MVLNN-bPZbiFxQV0atLdjcpKbtJm-wK_femtL14mRmYZ2bed6Zg5LzTAFxjdI8RlQ-RYV4QiHABEScFxGdggjmTMMeIj041KvAYTGNcI0QpI_wCjCnmCHOOJuDnI_hKVba1sbd1Vuu2hf1uozMVo125Trs-8yaL1q1aDfft7PNtDqPeZsaHrB-6FDtbB6_drw3-MLEJ3qSVbnUJzo1qo7465hn4fnr8WrzA5fvz62K-hLVAtIdVTWiOc9EUNTEyuRKES4IUUbIphGgqoZkRDBOqmCGSc4aMpEppg7kieUFn4O6wN13eDjr2ZWfjXq1y2g-xJETKZJ_lJKG3_9C1H4JL6hJVyFwIKvJE3Rypoep0U26C7VTYlafP0T8fs3Fr
CitedBy_id crossref_primary_10_3389_fgene_2021_708835
crossref_primary_10_1158_2326_6066_CIR_22_0121
crossref_primary_10_1186_s40779_022_00434_8
crossref_primary_10_1038_s41422_022_00627_9
crossref_primary_10_1002_ctm2_70396
crossref_primary_10_1016_j_crmeth_2022_100204
crossref_primary_10_1038_s42255_025_01296_9
crossref_primary_10_1093_bib_bbaf175
crossref_primary_10_3389_fpls_2023_1200014
crossref_primary_10_1038_s41421_023_00559_7
crossref_primary_10_1038_s41571_023_00830_6
crossref_primary_10_1038_s41467_023_39985_2
crossref_primary_10_1093_bib_bbaa433
crossref_primary_10_2217_fon_2023_0658
crossref_primary_10_1093_bib_bbaf207
crossref_primary_10_1101_gr_268581_120
crossref_primary_10_1038_s41586_025_09240_3
crossref_primary_10_1038_s43018_022_00414_w
crossref_primary_10_1016_j_humgen_2023_201236
crossref_primary_10_1038_s41467_022_30484_4
crossref_primary_10_1093_bib_bbad260
crossref_primary_10_1016_j_xpro_2024_103065
crossref_primary_10_1186_s13059_024_03272_0
crossref_primary_10_1016_j_gpb_2018_07_007
crossref_primary_10_1038_s41467_021_22008_3
crossref_primary_10_3390_a18040232
crossref_primary_10_1038_s41580_024_00768_2
crossref_primary_10_3390_cells12151970
crossref_primary_10_1016_j_prp_2025_156035
crossref_primary_10_1016_j_bbadis_2022_166534
crossref_primary_10_1093_procel_pwaf001
crossref_primary_10_1016_j_cels_2020_08_001
crossref_primary_10_1186_s13059_023_02951_8
crossref_primary_10_1016_j_csbj_2021_01_015
crossref_primary_10_1093_nargab_lqab102
crossref_primary_10_1186_s12864_020_07223_4
crossref_primary_10_1016_j_gpb_2023_06_003
crossref_primary_10_1186_s12859_022_04574_5
crossref_primary_10_1186_s13059_021_02422_y
crossref_primary_10_3390_ijms26062769
crossref_primary_10_1093_bib_bbab236
crossref_primary_10_1093_nar_gkad1023
crossref_primary_10_1371_journal_pcbi_1013354
crossref_primary_10_1093_nar_gkac320
crossref_primary_10_3389_fimmu_2021_679521
crossref_primary_10_1126_scitranslmed_abj0324
crossref_primary_10_1016_j_ccell_2021_08_011
crossref_primary_10_1093_biostatistics_kxac021
crossref_primary_10_3390_biom12101539
crossref_primary_10_3390_biomedicines9040368
crossref_primary_10_1186_s13059_024_03263_1
crossref_primary_10_1038_s41467_021_25725_x
crossref_primary_10_3390_biology14050479
crossref_primary_10_1016_j_isci_2025_112214
crossref_primary_10_1158_1078_0432_CCR_21_1593
crossref_primary_10_1016_j_tranon_2022_101557
crossref_primary_10_1016_j_yjmcc_2021_09_004
crossref_primary_10_1093_bib_bbab035
crossref_primary_10_1038_s41596_021_00561_x
crossref_primary_10_1093_bib_bbad179
crossref_primary_10_1016_j_cell_2024_06_023
crossref_primary_10_1016_j_pbi_2020_04_002
crossref_primary_10_1038_s41592_019_0534_4
crossref_primary_10_1080_21541264_2023_2200721
crossref_primary_10_1136_jitc_2023_008306
crossref_primary_10_1007_s11427_023_2561_0
crossref_primary_10_3390_biomedicines12061297
crossref_primary_10_1016_j_csbj_2025_07_026
crossref_primary_10_1109_ACCESS_2021_3052923
crossref_primary_10_3389_fcell_2025_1589823
crossref_primary_10_1038_s41467_024_46710_0
crossref_primary_10_1038_s41467_022_29744_0
crossref_primary_10_3390_life11070716
crossref_primary_10_3389_fimmu_2021_761890
crossref_primary_10_3390_biom13040611
crossref_primary_10_1186_s13059_020_02116_x
crossref_primary_10_3389_fonc_2021_796477
crossref_primary_10_1186_s13059_019_1830_0
crossref_primary_10_1016_j_csbj_2021_07_016
crossref_primary_10_1093_bib_bbac234
crossref_primary_10_1055_s_0041_1729970
crossref_primary_10_1038_s41467_020_18249_3
crossref_primary_10_1101_gr_276609_122
crossref_primary_10_1002_path_5511
crossref_primary_10_1093_bfgp_elaf010
crossref_primary_10_1126_science_adj1415
crossref_primary_10_1016_j_it_2024_09_010
crossref_primary_10_1186_s40779_024_00538_3
crossref_primary_10_1038_s42003_021_02208_9
crossref_primary_10_1016_j_cels_2021_08_012
crossref_primary_10_1186_s13073_023_01249_5
crossref_primary_10_1186_s12859_022_04703_0
crossref_primary_10_1093_nar_gkad874
crossref_primary_10_1016_j_csbj_2024_08_028
crossref_primary_10_1038_s41467_023_38919_2
crossref_primary_10_1093_nar_gkae442
crossref_primary_10_1038_s41598_025_87437_2
crossref_primary_10_1038_s41588_024_01724_8
crossref_primary_10_1038_s41422_020_0355_0
crossref_primary_10_1007_s11427_024_2770_x
crossref_primary_10_1016_j_csbj_2021_10_027
crossref_primary_10_1186_s13059_021_02480_2
crossref_primary_10_1088_1478_3975_abacfe
crossref_primary_10_1093_nar_gkab775
crossref_primary_10_1016_j_devcel_2023_08_023
crossref_primary_10_1093_bib_bbae720
crossref_primary_10_1093_nar_gkab931
crossref_primary_10_1186_s40779_022_00414_y
crossref_primary_10_1038_s41467_020_16905_2
crossref_primary_10_1186_s12915_023_01728_6
crossref_primary_10_3390_jpm11020149
crossref_primary_10_1038_s41598_021_04473_4
crossref_primary_10_1093_bib_bbab570
crossref_primary_10_1038_s41467_022_34870_w
crossref_primary_10_1038_s41467_022_28803_w
crossref_primary_10_1101_gr_278439_123
crossref_primary_10_1093_bib_bbab567
crossref_primary_10_3389_fimmu_2021_597651
crossref_primary_10_1038_s41596_021_00534_0
crossref_primary_10_1093_bib_bbae437
crossref_primary_10_1093_bioadv_vbae054
crossref_primary_10_32604_or_2023_044774
crossref_primary_10_1093_bib_bbab281
crossref_primary_10_1093_bib_bbaf243
crossref_primary_10_1186_s13059_021_02281_7
crossref_primary_10_1016_j_celrep_2025_115726
crossref_primary_10_1038_s41467_024_47152_4
crossref_primary_10_1038_s41598_023_39282_4
crossref_primary_10_1007_s12672_024_01406_1
crossref_primary_10_1186_s13059_022_02683_1
crossref_primary_10_1016_j_compbiomed_2023_107414
crossref_primary_10_1093_bib_bbab039
crossref_primary_10_1038_s41467_021_22851_4
crossref_primary_10_1038_s41586_022_05496_1
crossref_primary_10_3389_fcell_2021_767897
crossref_primary_10_3389_fonc_2021_719564
crossref_primary_10_1093_nar_gkaa183
crossref_primary_10_1186_s13024_022_00517_z
crossref_primary_10_1038_s41593_020_00736_x
crossref_primary_10_3389_fgene_2020_00490
crossref_primary_10_3389_frai_2022_842306
crossref_primary_10_1038_s41423_023_01112_y
crossref_primary_10_1038_s43587_023_00373_6
crossref_primary_10_1038_s42003_022_04093_2
crossref_primary_10_3390_genes11070792
crossref_primary_10_3389_fonc_2021_666829
crossref_primary_10_1016_j_csbj_2025_03_051
crossref_primary_10_1093_nar_gkab632
crossref_primary_10_1038_s42003_022_03900_0
crossref_primary_10_1002_JLB_6MR0522_685R
crossref_primary_10_1111_nph_18053
crossref_primary_10_1016_j_ygeno_2021_01_007
crossref_primary_10_1093_bib_bbad132
crossref_primary_10_1186_s12915_025_02128_8
crossref_primary_10_1038_s41467_024_48870_5
crossref_primary_10_1038_s41467_023_37439_3
crossref_primary_10_1016_j_gpb_2022_04_001
crossref_primary_10_1038_s42255_021_00388_6
crossref_primary_10_1093_bib_bbab105
crossref_primary_10_1101_gr_276868_122
crossref_primary_10_1093_bib_bbad006
crossref_primary_10_1158_2159_8290_CD_23_1380
crossref_primary_10_3389_fonc_2021_639013
crossref_primary_10_1186_s12859_021_04165_w
crossref_primary_10_1093_nar_gkaa394
crossref_primary_10_3390_life12020228
crossref_primary_10_1093_bioadv_vbad029
crossref_primary_10_1038_s41592_020_0825_9
crossref_primary_10_1109_JBHI_2024_3487174
crossref_primary_10_1038_s41596_020_0391_8
crossref_primary_10_1093_nar_gkac216
crossref_primary_10_1038_s41598_024_72204_6
crossref_primary_10_1093_bioinformatics_btae421
crossref_primary_10_1007_s11914_023_00840_4
crossref_primary_10_1186_s12859_024_05814_6
crossref_primary_10_1016_j_imlet_2022_04_008
crossref_primary_10_1146_annurev_biodatasci_020722_091857
crossref_primary_10_1016_j_csbj_2022_08_028
crossref_primary_10_1145_3641284
crossref_primary_10_1016_j_gpb_2022_06_006
crossref_primary_10_1016_j_stem_2020_12_012
crossref_primary_10_1016_j_cels_2021_09_004
crossref_primary_10_1038_s41467_021_22495_4
crossref_primary_10_1093_genetics_iyab019
crossref_primary_10_1038_s41587_021_01206_w
ContentType Journal Article
Copyright Copyright Nature Publishing Group Oct 2019
Copyright_xml – notice: Copyright Nature Publishing Group Oct 2019
DBID 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
DOI 10.1038/s41592-019-0529-1
DatabaseName 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 Collection
Hospital Premium Collection
Hospital Premium Collection (Alumni Edition)
ProQuest Central (Alumni) (purchase pre-March 2016)
ProQuest Materials Science & Engineering
ProQuest Central (Alumni)
ProQuest One Sustainability
ProQuest Central UK/Ireland
Advanced Technologies & Computer Science Collection
Agricultural & Environmental Science Collection
ProQuest Central Essentials
Biological Science Database
ProQuest Central
Technology Collection
Natural Science Collection
Earth, Atmospheric & Aquatic Science Database
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 Collection
ProQuest Health & Medical Complete (Alumni)
Materials Science Database
ProQuest Engineering Collection
Biological Sciences
Agricultural Science Database
Health & Medical Collection (Alumni Edition)
PML(ProQuest Medical Library)
Science Database
Algology Mycology and Protozoology Abstracts (Microbiology C)
Biological Science Database (ProQuest)
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 (retired)
ProQuest One Academic UKI Edition
ProQuest Central China
Engineering collection
Environmental Science Collection
ProQuest Central Basic
Genetics Abstracts
MEDLINE - Academic
DatabaseTitle 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
Agricultural Science Database
MEDLINE - Academic
Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: BENPR
  name: ProQuest Central
  url: https://www.proquest.com/central
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Biology
EISSN 1548-7105
EndPage 1015
ExternalDocumentID 31501550
Genre Research Support, Non-U.S. Gov't
Journal Article
GrantInformation_xml – fundername: NCI NIH HHS
  grantid: P30 CA008748
– fundername: Cancer Research UK (CRUK)
  grantid: C31893/A25050
GroupedDBID ---
-~X
0R~
123
29M
39C
4.4
53G
7X2
7X7
7XC
88E
88I
8AO
8CJ
8FE
8FG
8FH
8FI
8FJ
8R4
8R5
AAHBH
AARCD
AAYZH
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
ATHPR
AVWKF
AXYYD
AZFZN
AZQEC
BBNVY
BENPR
BGLVJ
BHPHI
BKKNO
BKSAR
BPHCQ
BVXVI
CCPQU
CGR
CS3
CUY
CVF
D1I
D1J
D1K
DB5
DU5
DWQXO
EBS
ECM
EE.
EIF
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
NFIDA
NNMJJ
NPM
O9-
ODYON
P2P
P62
PATMY
PCBAR
PDBOC
PHGZM
PHGZT
PJZUB
PPXIY
PQGLB
PQQKQ
PROAC
PSQYO
PTHSS
PYCSY
Q2X
RNS
RNT
RNTTT
SHXYY
SIXXV
SJN
SNYQT
SOJ
SV3
TAOOD
TBHMF
TDRGL
TSG
TUS
UKHRP
~8M
3V.
7QL
7QO
7SS
7TK
7U9
7XB
8FD
8FK
AGSTI
C1K
FR3
H94
K9.
M7N
P64
PKEHL
PQEST
PQUKI
PRINS
Q9U
RC3
7X8
PUEGO
ID FETCH-LOGICAL-c603t-bc237176d9c2f8415625820a2a8d966db6e4f64123a4f285540f83aaef15a2793
IEDL.DBID M7P
ISICitedReferencesCount 230
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000488225900031&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1548-7091
1548-7105
IngestDate Thu Oct 02 16:00:24 EDT 2025
Mon Oct 06 17:06:26 EDT 2025
Mon Jul 21 05:49:51 EDT 2025
IsDoiOpenAccess false
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 10
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c603t-bc237176d9c2f8415625820a2a8d966db6e4f64123a4f285540f83aaef15a2793
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ORCID 0000-0002-0487-9599
0000-0001-9203-6323
0000-0001-6402-523X
0000-0002-7606-089X
0000-0001-6782-8361
0000-0003-1981-5763
OpenAccessLink https://www.ncbi.nlm.nih.gov/pmc/articles/7485597
PMID 31501550
PQID 2298766367
PQPubID 28015
PageCount 9
ParticipantIDs proquest_miscellaneous_2288003472
proquest_journals_2298766367
pubmed_primary_31501550
PublicationCentury 2000
PublicationDate 2019-10-01
PublicationDateYYYYMMDD 2019-10-01
PublicationDate_xml – month: 10
  year: 2019
  text: 2019-10-01
  day: 01
PublicationDecade 2010
PublicationPlace United States
PublicationPlace_xml – name: United States
– name: New York
PublicationTitle Nature methods
PublicationTitleAlternate Nat Methods
PublicationYear 2019
Publisher Nature Publishing Group
Publisher_xml – name: Nature Publishing Group
SSID ssj0033425
Score 2.6628482
Snippet Single-cell RNA sequencing has enabled the decomposition of complex tissues into functionally distinct cell types. Often, investigators wish to assign cells to...
SourceID proquest
pubmed
SourceType Aggregation Database
Index Database
StartPage 1007
SubjectTerms Annotations
Automation
Cancer
Clustering
Computer simulation
Datasets
Gene expression
Gene Expression Profiling
Gene sequencing
Humans
Laboratories
Lymphoma
Lymphoma, Follicular - immunology
Lymphoma, Follicular - pathology
Mapping
Medical research
Ovarian cancer
Probabilistic models
Probability
Research centers
Ribonucleic acid
RNA
Sequence Analysis, RNA - methods
Single-Cell Analysis - methods
Stem cells
Tumor Microenvironment
Tumors
Title Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling
URI https://www.ncbi.nlm.nih.gov/pubmed/31501550
https://www.proquest.com/docview/2298766367
https://www.proquest.com/docview/2288003472
Volume 16
WOSCitedRecordID wos000488225900031&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LS8QwEB58ghffj9V1ieA12k3SJnsSVxRBLMUHLB5cYpuKoPvqruC_dybtqhe9eBkoaUub1_fN5EsG4DB7ihCEQse1bGZcmYACTVpxR6taCEhWudQnm9BxbDqdVlIF3IpKVjmdE_1EnfVTipEfC4HeMcJjpE8GQ05Zo2h1tUqhMQvzdEqC9NK9ZDoTS6l80lVi5VwjME5XNaU5LhC4SHdJW3hC0eLN3xmmR5qLlf9-4yosVxyTnZadYg1mXG8dFsuskx8b8JiMcBCTKJbOaGYUuucUiWXIo1-evTqA9XNGQYRXx6mY3cSnvHBDhgyXjSdvaN9IyPdjlxwrk3_jM5twf3F-d3bJqzQLPI0COeZPqZDo1EVZKxW5IYdOhMgLrLAmQ2cIW9OpPFIIcVblgmRtQW6ktS5vhlbg-N6CuV6_53aAaWcyBHwnTWaVcS2r87RpMqQJToaRMzWoTyuuW42VovtdazU4-CrGXk4_aHuuP6F7cJ4JpNKiBttl43QH5XEcXYmclhyt3b9fvgdLgprbC_HqMDceTdw-LKTv45di1IBZ3dHemgbMt8_j5AavrtpHaK-DK7Iiafju5e0t2ji5RpuED59PANPb
linkProvider ProQuest
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V3JTsMwEB0hFsGFfSmrkeBo0dpO7B4QQiwCAVWFQOJEMMkEIUELTQvip_hGZpIGuMCNA5dcnM3x5M0bz7MHYCO5DckJBSitriXSuCpPNFkjkbNa5JC8wTgvNmEbDXd1VW8OwHu5FoZllSUm5kCdtGOeI99SiqJjco-h3Xl6llw1irOrZQmNwixO8O2VQrZs-3ifxndTqcODi70j2a8qIOOwqrvyNlaaYpgwqccqdRy_qIDcoFfeJcT96eXRpKEhRPcmVaziqqZOe49pLfDK8uZLBPlDRCOUy6WCzRL5tTZ5kVeOAqQlR1xmUbXbyuhBrPPkJUOBqsvaz4w292yHE__tm0zCeJ9Di93C6KdgAFvTMFJU1Xybgetmh0CKRb-8B7Xg1ITkmWZBccL9Xa5-EO1U8CTJA0puFueNXZnhsyAGL7q9Rzo-slDx2ypAURQ3p2tm4fJPOjcHg612CxdAWHQJERrULvHGYd3bNK65hGgQ6iBEV4HlcqCiPhZk0dcoVWD9s5n-Yu6gb2G7x-cQjla1saoC84UxRE_FdiORJs7OgeTi7zdfg9Gji7PT6PS4cbIEY4pNLRcdLsNgt9PDFRiOX7r3WWc1N1oBN39tER_smCUu
linkToPdf http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LT9tAEB6hlFa9FCgtDY-yldrjKsnu2rs5IBQRokZBUYRA4lSzsccVEnkQJyD-Gr-OGTumXMqNAxdf1g-td3ZmvplvZwB-JsOQjFCA0upGIo2rc6DJGomc1SKD5A3GebMJ2--7i4vmYAUeyrMwTKssdWKuqJNJzDHymlKEjsk8hraWLmkRg3bncHojuYMUZ1rLdhqFiPTw_o7gW3bQbdNa_1Kqc3x29FsuOwzIOKzruRzGShOeCZNmrFLHWEYFZBK98i4hHEATQZOGhrS7N6liRlc9ddp7TBuBV5YLMZH6f2e5aHlOGxyUVkBrkzd8ZUQgLRnlMqOqXS2jDzHnk48PBaopG__3bnMr11l7y_9nHT4tfWvRKjbDBqzg-DO8L7pt3m_Cn8GMlBeTgbk2teCUheQItCD8cPU3Z0WISSo4eHKNkofFab8lM7wR5NmL-WJE1xETGJ-dDhRF03N65gucv8rkvkJlPBnjNxAWXUKODmqXeOOw6W0aN1xC7hHqIERXhd1y0aKljsiifytWhR9Pw7S7eYJ-jJMF30P6ta6NVVXYKgQjmhZlSCJNvjwDzO2XX74PH0gQopNuv7cDHxVLXc5F3IXKfLbAPViNb-dX2ex7Lr8CLl9bIB4BgIUt6w
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=Probabilistic+cell-type+assignment+of+single-cell+RNA-seq+for+tumor+microenvironment+profiling&rft.jtitle=Nature+methods&rft.au=Zhang%2C+Allen+W&rft.au=Ciara+O%E2%80%99Flanagan&rft.au=Chavez%2C+Elizabeth+A&rft.au=Lim%2C+Jamie+L+P&rft.date=2019-10-01&rft.pub=Nature+Publishing+Group&rft.issn=1548-7091&rft.eissn=1548-7105&rft.volume=16&rft.issue=10&rft.spage=1007&rft.epage=1015&rft_id=info:doi/10.1038%2Fs41592-019-0529-1&rft.externalDBID=HAS_PDF_LINK
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