Single-Cell Web Tools

Single Cell Web Tools

The Single Cell Web tool provides single-cell lncRNA-target annotation based on 31 single-cell RNA sequencing (scRNA-seq) datasets related to 21 human cancers (>500 cells). It provides interactive and customizable functions including two powerful modules:
(1) pan-cancer analysis module: graphically display the differences/similarities of lncRNA-target regulations among cancer types at the single-cell level.
(2) cancer-specific analysis module: reveal the cancer cell sub-populations specificity of lncRNA-target regulations and intra-tumor heterogeneity at the single-cell level.
In summary, from the perspective of pan-cancer and cancer-specific analysis, Single Cell Web Tools characterize lncRNA-target regulations from scRNA-seq datasets, including differential lncRNA-target regulations analysis, differential expression analysis, relevant functional states analysis, lncRNA-target networks, cell clustering maps, distribution in diverse cell populations and in sub-populations. View our Help page for further help.

Pan-cancer analysis module

Differential regulations in diverse cell populations

This function provides the differential analysis of different lncRNA-target regulation activity scores in 31 single-cell datasets containing 21 human diseases. Differential lncRNA-target regulation in a given single-cell dataset was identified by comparison with other single-cell datasets.

Differential expression analysis

This function provides the landscape of differential expression of lncRNAs and target genes across 31 single-cell datasets with 21 human cancers.

Functional states analysis

This function provides the landscape of differential lncRNA-target regulations associated with a given cell state across 31 single-cell datasets with 21 human cancers. Differential lncRNA-target regulations with a given cell state in a given single-cell data set were identified by comparing with other single-cell data sets.

Cancer-specific analysis module

Differential regulations in sub-populations

This function provides the differences in the distribution of lncRNA-target regulation activity scores among cancer cell sub-populations. It will help to understand the roles of lncRNA-target regulations in intra-tumor heterogeneity at the single-cell level.

Differential expression analysis

This function provides the differential expression of lncRNAs and target genes across cancer cell sub-populations.

Functional states analysis

This function provides the activity scores of differential lncRNA-target regulations associated with a given cell state among cancer cell sub-populations in a single-cell data sets.

Information of single cell datasets

ID	Cancer Type	Cell Number	lncRNA-Target number	Source	Accession	Cell Type
(UM)GSE139829	Uveal melanoma	42230	2040	Tissue: Eye	GSE139829	Neurons,Tissue_stem_cells,T_cells,Macrophage
(NSCLC)GSE143423_Met1	Non-small Cell Lung Cancer	13382	952	Tissue: Brain	GSE143423	Epithelial_cells,Macrophage,NK_cell
(UCEC)GSE139555_Uterus	Endometrial adenocarcinoma	12758	48	Tissue: Endometrium	GSE139555	Pre-B_cell_CD34-,Epithelial_cells,T_cells
(CRC)GSE139555_Colon	Colorectal cancer	10112	378	Tissue: Colon	GSE139555	B_cell,T_cells,NK_cell,CMP,Monocyte,Neurons,Chondrocytes
(NSCLC)GSE143423_Met2	Non-small Cell Lung Cancer	9595	804	Tissue: Brain	GSE143423	Epithelial_cells,Macrophage,Endothelial_cells,Tissue_stem_cells,Astrocyte
(PAAD)GSE112845	Pancreatic cancer	8321	1198	Cell Line: KLM1	GSE112845	MT-ND2+ Epithelial_cells,FOXM1+ Epithelial_cells,LRRC75A+ Epithelial_cells,SPP1+ Epithelial_cells,NUPR1+ Epithelial_cells,DHRS2+ Epithelial_cells,UPP1+ Epithelial_cells,KRTAP3-1+ Epithelial_cells,UBE2T+ Epithelial_cells
(PDAC)PRJCA001063_IB	Pancreatic Ductal Adenocarcinoma	8202	804	Tissue: Head	PRJCA001063	Tissue_stem_cells,Endothelial_cells,T_cells,Monocyte,B_cell,Epithelial_cells
(ARMS)GSE113660	Alveolar rhabdomyosarcoma	6875	887	Cell Line: Rh41	GSE113660	Neurons,MSC
(PDAC)PRJCA001063_IIA	Pancreatic Ductal Adenocarcinoma	6289	958	Tissue: Head	PRJCA001063	Epithelial_cells,Monocyte,Tissue_stem_cells,Chondrocytes,Pre-B_cell_CD34-,T_cells
(HNSC)GSE103322	Head and neck cancer	5902	2151	Tissue: Lymph node	GSE103322	Monocyte,T_cells,Endothelial_cells,Epithelial_cells,Fibroblasts,Chondrocytes,Tissue_stem_cells,Astrocyte,B_cell
(ATC)GSE148673	Anaplastic Thyroid Cancer	5861	583	Tissue: Fresh tumor	GSE148673	T_cells,B_cell,NK_cell,Monocyte,Fibroblasts
(OV)E-MTAB-8559_IIIB	Ovarian Carcinoma	5846	1507	Tissue: Peritoneal fluid	E-MTAB-8559	Smooth_muscle_cells,Neurons,Fibroblasts,Tissue_stem_cells,MSC,Endothelial_cells
(MPAL)GSE139369	Mixed-phenotype Acute Leukemia	5643	385	Tissue: Bone Marrow	GSE139369	Monocyte,CMP,Platelets
(PDAC)PRJCA001063_IIB	Pancreatic Ductal Adenocarcinoma	5263	1046	Tissue: Body and tail	PRJCA001063	Chondrocytes,T_cells,Macrophage,Monocyte,Epithelial_cells,Fibroblasts,Tissue_stem_cells,NK_cell,Smooth_muscle_cells,Endothelial_cells
(NSCLC)GSE143423_Met3	Non-small Cell Lung Cancer	5169	1350	Tissue: Brain	GSE143423	Macrophage,Tissue_stem_cells,Epithelial_cells,Monocyte,T_cells,NK_cell,Astrocyte
(OV)E-MTAB-8559_IIIC	Ovarian Carcinoma	5046	1588	Tissue: Peritoneal fluid	E-MTAB-8559	MSC,Smooth_muscle_cells,Fibroblasts,Tissue_stem_cells,Embryonic_stem_cells,Epithelial_cells
(SARC)GSE146221_CHLA9	Ewing sarcoma	4865	1421	Cell Line: CHLA9	GSE146221	AL844908.1+ Neurons,AC103706.1+ Neurons,TAGLN+ Neurons,PIF1+ Neurons,FAM111B+ Neurons,HDAC10+ Neurons
(SKCM)GSE72056	Melanoma	4645	2021	Tissue: Skin	GSE72056	B_cell,T_cells,Epithelial_cells,Neurons,Tissue_stem_cells,Endothelial_cells,Monocyte
(SARC)GSE146221_CHLA10	Ewing sarcoma	4632	1033	Cell Line: CHLA10	GSE146221	Neuroepithelial_cell,iPS_cells,MSC,Neurons
(BLCA)GSE130001	Bladder cancer	4129	718	Tissue: Bladder	GSE130001	Endothelial_cells,Epithelial_cells,Keratinocytes,Chondrocytes,Tissue_stem_cells
(CHOL)GSE125449	Intrahepatic cholangiocarcinoma	3835	703	Tissue: Liver	GSE125449	T_cells,Monocyte,Endothelial_cells,Hepatocytes,B_cell,Tissue_stem_cells
(SARC)GSE146221_TC71	Ewing sarcoma	3673	1240	Cell Line: TC71	GSE146221	Neurons,iPS_cells
(NSCLC)E-MTAB-6149	Non-small cell lung cancer	3524	910	Tissue: Lung	E-MTAB-6149	Epithelial_cells,Embryonic_stem_cells,T_cells,iPS_cells
(NET)GSE140312	Gastrointestinal Neuroendocrine Cancer	3158	364	Tissue: Liver	GSE140312	Endothelial_cells,Fibroblasts,Hepatocytes,Neurons,Monocyte
(HGG)GSE103224	High-grade glioma	2772	1035	Tissue: Brain	GSE103224	Neuroepithelial_cell,Chondrocytes,Astrocyte
(OV)GSE118828	Ovarian cancer	1909	945	Tissue: Ovary	GSE118828	NK_cell,Epithelial_cells,Monocyte,Tissue_stem_cells,Fibroblasts
(CML)GSE76312-Tissue Bone marrow	Chronic myelogenous leukemia	1877	1908	Tissue: Bone marrow	GSE76312	CMP,Pro-B_cell_CD34+
(AML)GSE110499	Acute myeloid leukemia	1184	592	Tissue: Bone marrow	GSE110499	B_cell,Monocyte,T_cells,MEP
(GBM)GSE84465	Glioblastoma	991	2099	Tissue: Brain	GSE84465	Astrocyte,Tissue_stem_cells
(GBM)GSE57872-Tissue Brain	Glioblastoma	623	2010	Tissue: Brain	GSE57872	ZMAT5+ Astrocyte,OLIG2+ Astrocyte,TOP2A+ Astrocyte,LMX1B+ Astrocyte,SMYD2+ Astrocyte,SAA2+ Astrocyte,NNAT+ Astrocyte
(MEL)GSE99330	Melanoma	575	1669	Cell Line: WM989	GSE99330	Neurons,T_cells
(BRCA)GSE77308	Breast cancer	369	2712	PDX	GSE77308	MSC,Epithelial_cells
(BRCA)GSE75688	Breast cancer	317	2885	Tissue: Breast	GSE75688	Epithelial_cells,B_cell
(ESCC)GSE81812	Esophageal squamous cell carcinoma	314	2818	Cell Line: KYSE-180	GSE81812	RSPH10B+ Epithelial_cells,CYP24A1+ Epithelial_cells,LINC00954+ Epithelial_cells,CTA-292E10.8+ Epithelial_cells,PIF1+ Epithelial_cells
(MEL)GSE81383	Melanoma	307	2403	Tissue: Skin	GSE81383	iPS_cells,Neurons
(CRC)GSE81861-Tissue Colon	Colorectal cancer	290	1639	Tissue: Colon	GSE81861	PDCD11+ Epithelial_cells,SLITRK6+ Epithelial_cells,TNFRSF11B+ Epithelial_cells,CENPQ+ Epithelial_cells
(CML)GSE98734	Chronic myelogenous leukemia	267	2273	Cell Line: K562	GSE98734	CTH+ BM & Prog.,USO1+ BM & Prog.,CCNO+ BM & Prog.,RP11-474I11.8+ BM & Prog.,ATP8B2+ BM & Prog.,BAHD1+ BM & Prog.
(LUAD)DRP001358	Lung adenocarcinoma	245	2660	Cell Line: LC-2/ad	DRP001358	H19+ Epithelial_cells,HMMR+ Epithelial_cells,AGAP1-IT1+ Epithelial_cells,C8orf47+ Epithelial_cells
(LUAD)DRP003337	Lung adenocarcinoma	218	1923	Cell Line: A549	DRP003337	Epithelial_cells,Smooth_muscle_cells
(GBM)GSE57872	Glioblastoma	177	3487	Cell Line: GSC/DGC	GSE57872	LA16c-366D1.3+ Astrocyte,UBB+ Astrocyte,LSM11+ Astrocyte,CYTL1+ Astrocyte
(NSCLC)DRP003981-Cell Line PC-9	Non-small cell lung cancer	164	2661	Cell Line: PC-9	DRP003981	RAB3IL1+ Epithelial_cells,NUPR1+ Epithelial_cells,CEP152+ Epithelial_cells
(PC)GSE99795	Prostate cancer	144	2381	Cell Line: LNCaP	GSE99795	iPS_cells,Epithelial_cells
(CCA)ERP020478	Cervix cancer	126	3360	Cell Line: Hela	ERP020478	MSC,Epithelial_cells
(LUAD)GSE69405-PDX	Lung adenocarcinoma	126	2458	PDX	GSE69405	Epithelial_cells,Endothelial_cells
(CRC)GSE51254	Colorectal cancer	99	2271	Cell Line: HCT-116	GSE51254	Epithelial_cells,iPS_cells
(BCA)DRP003981	Bronchoalveolar carcinoma	96	1872	Cell Line: H1650	DRP003981	Epithelial_cells
(NSCLC)DRP003981-Cell Line H1975	Non-small cell lung cancer	96	1929	Cell Line: H1975	DRP003981	TFPI2+ Epithelial_cells,HLA-DPA1+ Epithelial_cells
(NSCLC)DRP003981-Cell Line H2228	Non-small cell lung cancer	96	1967	Cell Line: H2228	DRP003981	RACGAP1+ Epithelial_cells,DYNLL1+ Epithelial_cells
(LUAD)DRP003981-Cell Line II18	Lung adenocarcinoma	96	2302	Cell Line: II18	DRP003981	S100A9+ Epithelial_cells,DGKA+ Epithelial_cells,CTD-2636A23.2+ Epithelial_cells
(MLPS)E-MTAB-6142	Myxoid liposarcoma	96	1769	Cell Line: MLS 1765-92	E-MTAB-6142	AURKA+ MSC,RIBC2+ MSC
(PDAC)GSE99305	Pancreatic ductal adenocarcinoma	96	1998	Cell Line: Pancreatic ductal adenocarcinoma cell lines	GSE99305	NUF2+ Epithelial_cells,TP53INP2+ Epithelial_cells
(CML)GSE76312	Chronic myelogenous leukemia	91	1714	Cell Line: K562	GSE76312	LRRC16A+ BM & Prog.,AHSP+ BM & Prog.
(MEL)GSE97681-Cell Line WM983B	Melanoma	86	3358	Cell Line: WM983B	GSE97681	CTB-151G24.1+ Neurons,RP11-542A14.2+ Neurons,POSTN+ Neurons
(RCC)GSE73121	Renal cell carcinoma	83	2403	PDX	GSE73121	PAEP+ Epithelial_cells,G0S2+ Epithelial_cells
(LUAD)GSE81861-Cell Line A549	Lung adenocarcinoma	74	1422	Cell Line: A549	GSE81861	Epithelial_cells
(CML)GSE81861	Chronic myelogenous leukemia	73	1831	Cell Line: K562	GSE81861	BM & Prog.,MEP
(BRCA)GSE75367	Breast cancer	70	2389	CTC	GSE75367	Epithelial_cells,Platelets
(HCC)GSE103866	Hepatocellular carcinoma	55	2031	Cell Line: HuH-7	GSE103866	iPS_cells
(CRC)GSE81861-Colorectal cancer	Colorectal cancer	51	1679	Cell Line: HCT-116	GSE81861	Embryonic_stem_cells
(CML)GSE69405	Chronic myelogenous leukemia	50	2168	Cell Line: K562	GSE94979	Epithelial_cells
(LUAD)GSE94979	Lung adenocarcinoma	50	1081	Cell Line: H358	GSE69405	BM & Prog.
(NSCLC)GSE81861-Cell Line H1437	Non-small cell lung cancer	47	1238	Cell Line: H1437	GSE81861	Neuroepithelial_cell,BM & Prog.
(LUAD)DRP001358-Cell Line PC-9	Lung adenocarcinoma	46	2411	Cell Line: PC-9	DRP001358	Epithelial_cells
(LUAD)DRP001358-Cell Line VMRC-LCD	Lung adenocarcinoma	46	2008	Cell Line: VMRC-LCD	DRP001358	iPS_cells
(BRCA)GSE91395	Breast cancer	45	422	Cell Line: MCF-7	GSE91395	HMGB1+ Epithelial_cells,DHRS2+ Epithelial_cells
(HCC)GSE103866-Cell Line HuH-1	Hepatocellular carcinoma	43	1927	Cell Line: HuH-1	GSE103866	Hepatocytes
(NB)GSE90683	Neuroblastoma	36	3014	Cell Line: Neuroblastoma cell line	GSE90683	Neurons
(MEL)GSE97681-Cell Line WM989	Melanoma	36	3289	Cell Line: WM989	GSE97681	Neurons,MSC
(RCC)GSE73121-Tissue Kidney	Renal cell carcinoma	35	2050	Tissue: Kidney	GSE73121	Epithelial_cells
(BRCA)GSE91395-Cell Line MDA-MB-231	Breast cancer	33	374	Cell Line: MDA-MB-231	GSE91395	MSC
(HCC)GSE65364	Hepatocellular carcinoma	26	778	Tissue: Liver	GSE65364	Hepatocytes
(AML)E-MTAB-2672	Acute myeloid leukemia	24	2587	Tissue: Bone marrow	E-MTAB-2672	GMP
(ALL)GSE100694	Acute lymphoblastic leukemia	24	3394	Cell Line: LOUCY/JURKAT	GSE100694	Pro-B_cell_CD34+

Differential regulations in diverse cell populations

This function provides the landscape of the proportion of cells with high activity scores (> 0.5*max (AUC scores)) for differential lncRNA-target regulations in cells across 31 single-cell datasets with 21 human cancers. Wilcoxon rank sum test was used to identify differential lncRNA-target regulations by comparing the activity scores between a given scRNA-seq and other scRNA-seq datasets.

scRNA-seq Dataset: Select a cancer single-cell data set to obtain differential lncRNA-target regulations.

LncRNA/Gene Symbol: Select a lncRNA to obtain lncRNA-target regulations for analysis.

scRNA-seq Dataset:

LncRNA/Gene Symbol:

The landscape of the cell proportion of differential lncRNA-target regulations

Analysis of differences between single-cell datasets

Table Result of associated lncRNA-target regulations

Differential expression analysis

This function provides the landscape of differential expression of lncRNAs and target genes across 31 single-cell datasets with 21 human cancers. Wilcoxon rank sum test was used to identify differential lncRNA and genes by comparing expression levels between a given scRNA-seq and other scRNA-seq datasets.

scRNA-seq Dataset: Select a cancer single-cell data set for differential expression analysis.

LncRNA/Gene Symbol: Select a lncRNA for differential expression analysis.

scRNA-seq Dataset:

LncRNA/Gene Symbol:

The landscape of differential expression of lncRNAs and target genes

Table Result of associated Expression

Differential expression of lncRNAs and target genes

Table Result of associated lncRNA-target regulations

Functional states analysis

This function provides the landscape of the proportion of cells with high activity scores (> 0.5*max (AUC scores)) for differential lncRNA-target regulations associated with a given cell state (such as stemness, epithelial-mesenchymal transition, angiogenesis and inflammation) across 31 single-cell datasets with 21 human cancers. Wilcoxon rank sum test was used to identify differential lncRNA-target regulations by comparing the activity scores between a given cell functional state and other cell functional states.

scRNA-seq Dataset: Select a cancer single-cell data set for differential regulation analysis.

Cell functional states: Select a cancer single-cell data set for differential regulation analysis.

LncRNA/Gene Symbol: Select a lncRNA for drawing the point diagram.

scRNA-seq Dataset:

Cell States:

LncRNA/Gene Symbol:

The landscape of the cell proportion of differential lncRNA-target regulations associated with cell state

Analysis of differences between single-cell datasets

Table Result of associated lncRNA-target regulations

Differential regulations in sub-populations

This function provides the differences in the distribution of lncRNA-target regulation activity scores among cancer cell sub-populations and shows the proportion of cells with high activity scores (> 0.5*max (AUC scores)). It will help to understand the roles of lncRNA-target regulations in intra-tumor heterogeneity at the single-cell level. Wilcoxon rank sum test was used to identify differential lncRNA-target regulations by comparing the activity scores between a given cancer cell sub-population and other cancer cell sub-populations.

scRNA-seq Dataset: Select a cancer single-cell data set for analysis.

Cancer cell sub-populations: Select a cancer cell sub-population for differential regulations analysis.

LncRNA/Gene Symbol: Select a lncRNA to obtain key lncRNA-target regulations for analysis.

scRNA-seq Dataset:

Cell Subtype:

LncRNA/Gene Symbol:

The landscape of the cell proportion of differential lncRNA-target regulations

Analysis of differences between cell subtypes

Table Result of associated lncRNA-target regulations

Differential expression analysis

This function provides the differential expression of lncRNAs and target genes across cancer cell sub-populations. Wilcoxon rank sum test was used to analyze the differential expression of lncRNA and its target genes in different cancer cell sub-populations.

LncRNA: Select a lncRNA for differential expression analysis.

scRNA-seq Dataset: Select a cancer single-cell data set for analysis.

Cancer cell sub-populations: Select a cancer cell sub-population for differential regulations analysis.

LncRNA/Gene Symbol: Select a lncRNA for differential expression analysis.

scRNA-seq Dataset:

Cell Subtype:

LncRNA/Gene Symbol:

The landscape of differential expression of lncRNAs and target genes

Table Result of associated genes

Differential expression box-plot

Table Result of associated lncRNA-target regulations

Functional states analysis

This function provides the cell proportion with high activity scores (> 0.5*max (AUC scores)) of differential lncRNA-target regulations associated with a given cell state (such as stemness, epithelial-mesenchymal transition, angiogenesis and inflammation) among cancer cell sub-populations in a single-cell data sets. Wilcoxon rank sum test was used to identify differential lncRNA-target regulations by comparing the activity scores between a given cell functional state and other cell functional states.

scRNA-seq Dataset: Select a cancer single-cell data set for analysis.

Cell functional states: Select a cell functional state for analysis.

LncRNA/Gene Symbol: Select a lncRNA to obtain key lncRNA-target regulations for analysis.

scRNA-seq Dataset:

Cell States:

LncRNA/Gene Symbol:

The landscape of the cell proportion of differential lncRNA-target regulations associated with cell state

Analysis of differences between cell subtypes

Table Result of associated lncRNA-target regulations