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Aggregate A35
177
Monocyte
Inflammation
M15.113
M12.10
M13.22
M13.1
M15.37
M14.28
M14.65
M15.26
M15.109
M15.105
Neutrophil
Protein Synthesis
Cytokine/
Chemokines
Blood module repertoire (Generation 3)
Click circles to zoom in & symbol to zoom out
Information:
Ontologies
transcription, DNA-templated
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M13.3.json.html
Transcripts (106): ACSS2, ANKRD33, APH1B, ATF6, ATG7, B9D2, C11ORF56, C14ORF94, C9ORF72, CBARA1, CD82, CENTD2, CFP, CORO1C, CSF2RA, CSF2RA, CTNNA1, CTSD, CUTL1, DDEF1, DIRC2, DJ341D10.1, EDEM2, ELL, ENTPD1, ERO1L, ETS2, ETV6, EXOC6, FAM100B, FAM129B, FBXO38, FERMT3, FKBP5, G6PD, GADD45A, GAS7, GBA, GBA, GBE1, GNA15, GNAI3, GNB2, HDAC4, HIATL1, HK2, HK2, HLX, HMGB2, HSDL2, IER3, IRS2, KBTBD7, KIAA0513, LOC644642, LOC728069, LPGAT1, LRRC25, LRRFIP2, LRRFIP2, LTB4R, MAP3K2, MAPK1, MEGF9, MICAL1, MSRA, MTX1, MVP, NBN, NDRG1, NLRX1, OPRL1, OSBPL8, OSCAR, P2RX1, PDK3, PFKFB3, PGM1, PHCA, PIM3, PLEKHO2, PLP2, PPP1R3D, PRAM1, QSOX1, RILPL2, RNF144B, RRAGD, RRP12, SHKBP1, SIRPA, SLC37A3, SORT1, SQRDL, TACC3, TBC1D2, TEF, THOC5, THOC5, TM6SF1, TMCO3, TMEM120A, WIPI1, YIPF1, YIPF1, ZBTB34
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M13.3
TBD
M13.3
Leukocytes RNAseq
Lit. Profiles:
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Acumenta Biotech
Literature Lab
http://www.acumenta.com/literature-lab-1
Red = strong association
Orange = moderate association
Hematopoiesis
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M13.3%20/Motif_data_table.html
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
ion transmembrane transport
Transcripts (19): ADORA2B, CACNA1E, CR1, EFEMP2, GPR141, GPR63, HS.162734, KIAA1026, KREMEN1, LOC643550, LOC646434, LOXL3, MAK, MERTK, SLC26A8, SLC26A8, TIFA, VDR, WWP2
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M16.98.json.html
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M16.98
TBD
M16.98
Leukocytes RNAseq
Lit. Profiles:
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Acumenta Biotech
Literature Lab
http://www.acumenta.com/literature-lab-1
Red = strong association
Orange = moderate association
Hematopoiesis
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
No result found for this module
RcisTarget
No result found for this module
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
transcription, DNA-templated
GSAn
Transcripts (27): CAPN3, CASP4, CCDC109A, CDS2, CEBPB, CNN2, DBN1, DNAJB12, DNAJC5, EXT1, FAM49B, FLJ10357, GAPDH, H2AFY, HIST1H2BD, IFITM2, IL10RB, LILRA5, MAFG, MTMR3, PITPNM2, PTTG1IP, PXN, PYCARD, RHOT1, SAT1, SPTLC2
https://ayllonbe.github.io/modulesV3/modules_results_html/M16.79.json.html
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M16.79
M16.79
Protein synthesis
Leukocytes RNAseq
Lit. Profiles:
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Acumenta Biotech
Literature Lab
http://www.acumenta.com/literature-lab-1
Red = strong association
Orange = moderate association
Hematopoiesis
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M16.79%20/Motif_data_table.html
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
cellular protein modification process
Transcripts (16): ATP6V0B, C20ORF24, C20ORF24, CD14, CLIC1, CYBA, EFHD2, EVI2B, FTHL7, GNS, IFNGR2, ITGB2, RAB7A, S100A4, SMAP2, TSPO
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M14.65.json.html
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M14.65
Monocytes
Benaroya ICSeq
Lit. Profiles:
Myeloid Lineage
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
Acumenta Biotech
Literature Lab
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
http://www.acumenta.com/literature-lab-1
Red = strong association
Orange = moderate association
Hematopoiesis
Myeloid
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M14.65%20/Motif_data_table.html
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
transcription by RNA polymerase II
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M15.26.json.html
Transcripts (40): ATP8B4, CDK5RAP2, CEACAM3, DSE, EGLN1, FKBP1A, GADD45B, GDPD3, GPR160, HPSE, IDI1, IL1RAP, KLHDC8B, LBR, LGALS8, LOC201175, LOC651143, LOC654053, MAEA, MCL1, MLSTD1, MTF1, PDLIM7, PIK3AP1, PLAUR, PLAUR, PLAUR, PPP1R12A, PREX1, RAB27A, REPS2, RHOT1, RNASEL, RP2, SIRPB1, SPOPL, TLR4, TPD52L2, TRPM6, VASP
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M15.26
Neutrophils
Benaroya ICSeq
Lit. Profiles:
Myeloid lineage
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
Acumenta Biotech
Literature Lab
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://www.acumenta.com/literature-lab-1
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Red = strong association
Orange = moderate association
Hematopoiesis
Myeloid
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M15.26%20/Motif_data_table.html
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
cellular protein modification process
Transcripts (23): AGTRAP, AGTRAP, BST1, C16ORF7, C20ORF3, DRAM, FCER1G, FLJ22662, FLOT1, ITGAM, KIF1B, LILRA3, LILRA3, METTL9, MMP25, NQO2, OSCAR, PGD, SERPINA1, SERPINA1, SLC2A3, SMARCD3, TSPO
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M14.28.json.html
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
xxxx
M14.28
Neutrophils
Benaroya ICSeq
Lit. Profiles:
Myeloid lineage / Sepsis
xxxxx
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
Acumenta Biotech
Literature Lab
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
http://www.acumenta.com/literature-lab-1
Red = strong association
Orange = moderate association
Hematopoiesis
Myeloid
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M14.28%20/Motif_data_table.html
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
transcription by RNA polymerase II
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M13.22.json.html
Transcripts (68): ACSL4, ADAM8, AGTPBP1, APBB1IP, BCL3, BRI3, C1RL, C5AR1, C6ORF166, CD58, CDA, CHSY1, CPD, CYB5R4, DENND3, DUSP1, EIF4E3, FCGR2A, FCGR2A, FCGR3B, FGR, FLJ20273, FPR1, GRINA, HCK, HSPA1A, IFNAR1, IL8RA, IMPA2, KIAA0247, KIAA1600, KIAA1754, LAMP2, LAT2, LITAF, LOC399744, LOC401357, LOC729021, LOC730820, LY96, MTMR3, N4BP1, NCF4, NFE2, NLRP12, NPL, NPL, NUMB, PGCP, PPP4R1, PSCD4, RALB, REPS2, RNF13, RNF149, RNF24, S100A11, SDCBP, SEPX1, SLC11A1, SOD2, SORL1, SPI1, SPI1, SRPK1, STX11, TRIB1, VNN2
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M13.22
xxxx
Neutrophils
Benaroya ICSeq
Lit. Profiles:
Neutrophils / Sepsis
xxxxx
Acumenta Biotech
Literature Lab
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
http://www.acumenta.com/literature-lab-1
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Red = strong association
Orange = moderate association
Hematopoiesis
Myeloid
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M13.22%20/Motif_data_table.html
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
organelle assembly
Transcripts (17): C9ORF72, CR1, CREB5, DGAT2, FCGR2A, FLJ14166, GNG10, IL1RN, IL6R, LOC552891, LOC650546, NAMPT, P2RY13, SDCBP, TLR8, TNFRSF10B, WDR52
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M15.109.json.html
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M15.109
Rheumatoid Arthritis, SLE Signaling
Inflammation
Benaroya ICSeq
Lit. Profiles:
Neutrophils
Arthritis
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
Acumenta Biotech
Literature Lab
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://www.acumenta.com/literature-lab-1
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Red = strong association
Orange = moderate association
Hematopoiesis
Myeloid
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
No result found for this module
RcisTarget
No result found for this module
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
protein transport
Transcripts (17): ATP6V0E1, ATP6V0E1, ATP6V1E1, C20ORF43, CHIC2, CHMP2A, FLJ10986, HBXIP, HCLS1, LILRB2, MAP3K3, MTX1, OAT, PSMB3, SRGN, TALDO1, TYROBP
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M15.105.json.html
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M15.105
xxxx
Inflammation
Benaroya ICSeq
Lit. Profiles:
Neutrohils / Sepsis
Myeloid Cells
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
Acumenta Biotech
Literature Lab
http://www.acumenta.com/literature-lab-1
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Red = strong association
Orange = moderate association
Hematopoiesis
Myeloid
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M15.105%20/Motif_data_table.html
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
M13.12
Signal transduction / Neutrophil degranulation
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M13.12.json.html
Transcripts (55): ACSL1, ADM, AIM2, ALPL, ANXA3, B4GALT5, C16ORF57, C19ORF59, C5ORF32, CA4, CEACAM1, CEACAM1, CLEC4D, CST7, DSC2, DYSF, F5, FCGR1A, FCGR1B, FOLR3, GYG1, HIST2H2AA3, HIST2H2AC, HK3, HPSE, HS.150808, HS.407903, IL18R1, IL18RAP, IL1RN, IRAK3, KCNJ15, KLHL2, LILRA5, LIMK2, LIN7A, LMNB1, LOC153561, LOC440731, LOC648984, LOC728519, MMP9, NLRC4, PFKFB3, PGS1, PROK2, RGL4, S100A12, SIGLEC5, SIPA1L2, SLC22A4, SLC22A4, SLC26A8, TLR5, TNFAIP6, VNN1, ZNF438
Inflammation
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
Inflammation
M13.12
Summary: Ontology, pathway and literature keyword enrichment all point to a core group of genes constituting this module being strongly associated with inflammation and in some cases more specifically inflammasomes.
Examples of genes most prominently associated with inflammation, NOD-Like Receptor and Toll-like receptor pathways include IRAK3, TLR5, IL18R1, IL18RAP, IL1RN, as well as the inflammasomes molecules AIM2 and NLRC4 (literature clusters 1 &2).
Other annotations mention phagocytes and myeloid cells as well as host-pathogen interaction (literature clusters 3 & 4). This fits well with leukocyte transcript restriction data since abunance of the transcripts forming this module is particularly elevated in neutrophils as well as monocytes in the context of sepsis.
Leukocytes RNAseq
Lit. Profiles:
Neutrophils / Sepsis
inflammation
Acumenta Biotech
Literature Lab
Functional gene clusters and associated terms
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
http://www.acumenta.com/literature-lab-1
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Red = strong association
Orange = moderate association
Expression:
Hematopoiesis
Neutrophils & Sepsis
Myeloid
Summary: Leukocyte RNAseq data shows predominant expression in neutrophils (all transcripts, except AIM2, HPSE and PFKFB3), with higher levels observed in monocytes of septic patients as well for about 50% of the transcripts in this module. In the hematopoiesis dataset about a third of the transcripts show higher levels of expression in cord blood monocytes and granulocytes.
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M13.12%20/Motif_data_table.html
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Ontologies
transcritpion by RNA polymerase II
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M12.10.json.html
Information:
Transcripts (53): ABTB1, ALOX5, ATG16L2, C10ORF54, CEBPD, CENTD3, CRISPLD2, CXCL16, EDG4, EMR2, FAM53C, FRAT2, GALNAC4S-6ST, IGF2R, IGSF6, IL13RA1, ITGAX, LAMP2, LILRB3, MBD6, MBOAT7, MXD1, MYO1F, NARF, NCF1C, NDEL1, NUMB, PFKFB4, PILRA, RAB24, RAF1, RNF130, RTN3, SIRPA, SKAP2, SLC12A9, SLC25A44, SSH2, STX3, SVIL, TBXAS1, TIMP2, TLR8, TMEM71, TNFRSF1A, TSEN34, TSEN34, UBN1, ULK1, ULK1, USP10, XPO6, ZNF467, ZNF746, ZYX
Gene symbols and identifiers for this module are also available in supplementary file
M12.10
Pathways:
xxxx
Inflammation
Lit. Profiles:
Leukocytes RNAseq
Neutrophils / sepsis
Phagocytosis / Autophagy / Arachidonic Acid
Acumenta Biotech
Literature Lab
http://www.acumenta.com/literature-lab-1
Red = strong association
Orange = moderate association
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Hematopoiesis
Erytrhoid / Monocytes / Neutrophils
Expression
Transcription factor binding
Motif Enrichment
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M12.10%20/Motif_data_table.html
RcisTarget Reference Web page
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
Information:
Ontologies
cellular protein modification process
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M15.113.json.html
Transcripts (16): AATK, BMX, DNAH5, FUT7, GALNT14, HS.246177, IL1R1, KIAA0329, KIAA1026, LOC728744, MAPK14, NAIP, NAIP, RAB20, RASGRP4, SOCS3, ZDHHC19
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M15.113
Inflammation
Inflammation
Leukocytes RNAseq
Lit. Profiles:
Neutrophils / Sepsis
Inflammation
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
Acumenta Biotech
Literature Lab
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://www.acumenta.com/literature-lab-1
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Red = strong association
Orange = moderate association
Hematopoiesis
Erythroid
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
No result found for this module
RcisTarget
No result found for this module
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
cellular protein modification process
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M15.37.json.html
Transcripts (33): ALDOA, BICD2, CD151, CLEC12A, FAM129A, FERMT3, FPR2, FTHL2, GNG10, GPSM3, HIST1H2AC, HSD17B11, IL1B, LAT2, LOC440093, LRCH4, MX2, NCF2, NDUFB3, NDUFB3, NT5C2, RHBDF2, RTN3, SERPINB1, SH3GLB1, SLC16A3, SOD2, STXBP2, TMEM154, TNFSF10, TSPO, VNN2, WARS, WSB1
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M15.37
xxxx
Inflammation
Leukocytes RNAseq
Lit. Profiles:
Myeloid Lineage
xxxxx
Acumenta Biotech
Literature Lab
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
http://www.acumenta.com/literature-lab-1
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Red = strong association
Orange = moderate association
Hematopoiesis
Neutrophils / Monocytes
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M15.37%20/Motif_data_table.html
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
Activation of innate immune response
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M13.1.json.html
Transcripts (137): ABTB1, ACAA1, ACSS2, AIF1, ANKRD13A, AOAH, APAF1, ARHGAP9, ARID3A, ATP6V0D1, AXUD1, C17ORF62, C20ORF24, C9ORF19, CAB39, CAPZA2, CASP1, CD300A, CD55, CDKN2D, CHMP2A, CKLF, CLEC12A, CLEC12A, CLEC4A, CLEC4A, CNIH4, CSNK1D, CYP4F3, DHRS7, E2F3, EDG6, EHD1, FBXL5, FES, FGR, FKBP1A, FLOT2, FTH1, FTHL11, FTHL3, G6PD, GAPDH, GRN, GRN, HIST1H2BK, HMGB2, HSPA1B, IFNGR1, IL10RB, IMPDH1, IQGAP1, KIAA1949, LAMP2, LAMP2, LAMP2, LILRA2, LMO2, LOC730744, LRP10, LST1, LST1, M6PRBP1, MAPK1, MAPK3, MGC4677, MIDN, MLKL, MS4A6A, MSRB2, MVP, MYD88, NADK, NBEAL2, NCSTN, NFKBIZ, NOLA3, NOTCH1, NRD1, OBFC2A, OSTF1, P2RY13, PACSIN2, PADI4, PARP9, PCNX, PELI1, PELO, PHF21A, PICALM, PLOD1, PPM1M, PPP1R15A, PPP2R5A, PRCP, PRCP, PRKCD, PTEN, PTPN12, PTPRE, PTPRE, PYCARD, RAB24, RAB32, RAB6IP1, RARA, RASSF2, RBMS1, RPS6KA1, RXRA, S100A6, SELL, SFXN4, SIGLEC10, SLA, SLC15A3, SLC15A4, SLC31A2, SLC40A1, SLC9A1, SMAP2, SNX27, STAT3, STAT5B, STX10, SYK, TBC1D14, TBL1X, TCIRG1, TIMP1, TKT, TLN1, TMEM91, TNFRSF1B, TNFSF13B, TOM1, TPD52L2, TPST2, TST, TXN, TXN, USP3, ZFP106, ZFP106, ZFP36, ZMIZ1, ZYX
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M13.1
xxxx
Inflammation
Leukocytes RNAseq
Lit. Profiles:
Myeloid lineage & sepsis
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
xxxxx
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Acumenta Biotech
Literature Lab
http://www.acumenta.com/literature-lab-1
Red = strong association
Orange = moderate association
Hematopoiesis
Mixed
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M13.1%20/Motif_data_table.html
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
Protein phosphorylation
Transcripts (20): FCAR, HS.130245, HS.163346, HS.559151, HS.572130, KIAA1881, KIF1B, LIMK2, LOC401233, LOC651612, MANSC1, MAPK14, OPLAH, OSM, PSG3, RASGRP4, S100P, SLC2A14, ST3GAL4, TLR2
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M15.84.json.html
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M15.84
IL6 Cytokine Signaling
Cytokines / Chemokines
M15.84
Lit. Profiles:
Leukocytes RNAseq
Neutrophils
Inflammatory cytokines
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
Acumenta Biotech
Literature Lab
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
http://www.acumenta.com/literature-lab-1
Red = strong association
Orange = moderate association
Hematopoiesis
-
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Drug targets:
Transcription factor binding
Motif Enrichment
https://www.targetvalidation.org/
https://www.targetvalidation.org/summary?targets=186431,94914,167676,54523,182541,111261,112062,178814,99985,221826,171777,163993,173262,110080,137462
https://www.targetvalidation.org/target/ENSG00000112062?view=sec:tractability
Immune Cell Types RNAseq
(Monaco et al., 2019)
No result found for this module
RcisTarget
No result found for this module
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
Innate Immune Response
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M13.16.json.html
Transcripts (39): ALPK1, AQP9, BASP1, BCL6, BTNL8, CASP4, CASP5, CR1, CREB5, CSF2RB, FBXL13, FFAR2, FPR2, GK, GK, GPR109A, GPR109B, GPR97, GPR97, GPR97, IL8RB, KCNJ15, KCNJ2, KRT23, LIMK2, LOC641710, LOC642103, LOC642684, LOC652578, LOC728417, LOC728417, LRG1, MAK, MCTP2, MGAM, NAMPT, NCF4, NSUN7, PYGL, RNF149, SLPI, STEAP4, TLR6
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M13.16
xxxx
Cytokines / Chemokines
M13.16
Leukocytes RNAseq
Lit. Profiles:
Neutrophils
xxxxx
Acumenta Biotech
Literature Lab
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
http://www.acumenta.com/literature-lab-1
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Red = strong association
Orange = moderate association
Hematopoiesis
Myeloid
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M13.16%20/Motif_data_table.html
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
cellular protein modification process
Transcripts (20): AGPAT2, ALDOA, ARHGEF11, BLOC1S1, C9ORF89, CTDP1, DNM2, FMNL1, GAA, GLT25D1, IIP45, LOC642489, LRPAP1, MYADM, OS9, PIK3CD, PKM2, RGS19, SH3BP5L, ZDHHC12
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M15.81.json.html
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M15.81
TBD
M15.81
Leukocytes RNAseq
Lit. Profiles:
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Acumenta Biotech
Literature Lab
http://www.acumenta.com/literature-lab-1
Red = strong association
Orange = moderate association
Hematopoiesis
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M15.81%20/Motif_data_table.html
RcisTarget Reference Web page
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Ontologies
Information:
cellular protein modification process
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M15.43.json.html
Transcripts (30): CAMK2G, CLEC4E, COL18A1, COP1, CPEB4, DHRS13, FYB, GAST, GSN, HIP1, HIST1H2BE, HIST1H3D, HS.467586, LOC440900, LOC646144, LRRC25, MCTP1, MEFV, MGC18216, MTMR3, PGCP, PLXNC1, PTPRC, RCN3, STOM, SVIL, TLE3, TMEM176A, TNFSF14, TXNRD1
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M15.43
M15.43
TBD
Leukocytes RNAseq
Lit. Profiles:
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Acumenta Biotech
Literature Lab
http://www.acumenta.com/literature-lab-1
Red = strong association
Orange = moderate association
Hematopoiesis
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M15.43%20/Motif_data_table.html
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
organonitrogen compound metabolic process
Transcripts (21): AGPAT9, ANPEP, ATHL1, BEST1, C16ORF72, C5ORF41, CSF3R, CTBS, CTBS, CUEDC1, GABARAPL1, HS.34558, IL4R, LOC441124, LOC88523, MKNK1, MYBPC3, REM2, ROPN1L, SEMA4B, ZFAND3
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M15.78.json.html
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M15.78
M15.78
TBD
Leukocytes RNAseq
Lit. Profiles:
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Acumenta Biotech
Literature Lab
http://www.acumenta.com/literature-lab-1
Red = strong association
Orange = moderate association
Hematopoiesis
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
No result found for this module
RcisTarget
No result found for this module
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
transcription by RNA polymerase II
Transcripts (15): BAZ1A, CCPG1, CD53, CD53, CD58, CKLF, DDEF1, FAM45A, GLRX, MARCKS, MOSPD2, RHOT1, RNASEL, TLE4, YIPF4
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M14.74.json.html
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M14.74
M14.74
TBD
Leukocytes RNAseq
Lit. Profiles:
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Acumenta Biotech
Literature Lab
http://www.acumenta.com/literature-lab-1
Red = strong association
Orange = moderate association
Hematopoiesis
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M14.74%20/Motif_data_table.html
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Refernce Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Information:
Ontologies
transcription by RNA polymerase II
GSAn
https://ayllonbe.github.io/modulesV3/modules_results_html/M14.7.json.html
Transcripts (31): BATF, CPEB3, DHRS12, ECGF1, FBXL5, FKBP15, FLJ40448, GADD45A, GPR108, IPO11, JAK2, LOC255809, MFN2, MLKL, NEU1, PDZD8, PGM2, PHTF1, POR, RAB1A, RIN3, RIT1, SLC24A4, SLC36A1, SLC40A1, SLC9A8, TBC1D8, TFE3, TMEM185B, UNC13D, WSB2
Gene symbols and identifiers for this module are also available in supplementary file
Pathways:
M14.7
M14.7
TBD
Leukocytes RNAseq
Lit. Profiles:
Summary: This study compared whole transcriptome signatures of 6 immune cell subsets and whole blood from patients with an array of immune-associated diseases. Fresh blood samples were collected from healthy subjects and subjects diagnosed type 1 diabetes, amyotrophic lateral sclerosis, and sepsis, as well as multiple sclerosis patients before and 24 hours after the first treatment with IFN-beta. At the time of blood draw, an aliquot of whole blood was collected into a Tempus tube (Invitrogen), while the remainder of the primary fresh blood sample was processed to highly pure populations of neutrophils, monocytes, B cells, CD4 T cells, CD8 T cells, and natural killer cells. RNA was extracted from each of these cell subsets, as well as the whole blood samples, and processed into RNA sequencing (RNAseq) libraries (Illumina TruSeq). Sequencing libraries were analyzed on an Illumina HiScan, with a target read depth of ~20M reads. Reads were demultiplexed, mapped to human gene models (ENSEMBL), and tabulated using HTSeq. Read count data were normalized by the TMM procedure (edgeR package).
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
http://sepsis.gxbsidra.org/dm3/geneBrowser/show/4000098
Acumenta Biotech
Literature Lab
http://www.acumenta.com/literature-lab-1
Red = strong association
Orange = moderate association
Hematopoiesis
Expression
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
Transcription factor binding
Motif Enrichment
Immune Cell Types RNAseq
(Monaco et al., 2019)
RcisTarget
https://motoufiq.github.io/DC_Gen3_Module_Analysis/RcisTarget_Output_v1/M14.7%20/Motif_data_table.html
https://motoufiq.github.io/DC_Gen3_Module_Analysis/
RcisTarget Reference Web page
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
https://pubmed.ncbi.nlm.nih.gov/28991892/
https://www.bioconductor.org/packages/release/bioc/html/RcisTarget.html
Functional annotations
Module / Gene Composition
Aggregate A35
Immune Cell Types RNAseq
(Monaco et al., 2019)
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107011
Currently empty. Content coming soon!
Clinical
Relevance
Abundance profiles
Hematopoiesis
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759
https://www.ncbi.nlm.nih.gov/pubmed/21241896
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