Blue:RNA-Seq Analyses:PBMCs:20140523 PBMCs: Difference between revisions
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== Bicluster Analysis: | == Bicluster Analysis: Splitting Samples into two Groups == | ||
*To try and separate out single PBMC groupings prior to Singular analysis (requires comparison of at least two data sets) without using human Neurons | *To try and separate out single PBMC groupings prior to Singular analysis (requires comparison of at least two data sets) without using human Neurons |
Revision as of 19:14, 28 October 2014
Libraries
Group | Sample Name | Nextera_Ind | Seq Lane | Seq Run | Seq File 1 | Seq File 2 | Seq File 3 |
1 | 1_PBMC_C03 | 1 | 3,4,5 | HL170 | s_3_1_Indx01.txt.gz | s_4_1_Indx01.txt.gz | s_5_1_Indx01.txt.gz |
1 | 1_PBMC_C09 | 2 | 3,4,5 | HL170 | s_3_1_Indx02.txt.gz | s_4_1_Indx02.txt.gz | s_5_1_Indx02.txt.gz |
1 | 1_PBMC_C15 | 3 | 3,4,5 | HL170 | s_3_1_Indx03.txt.gz | s_4_1_Indx03.txt.gz | s_5_1_Indx03.txt.gz |
1 | 1_PBMC_C25 | 4 | 3,4,5 | HL170 | s_3_1_Indx04.txt.gz | s_4_1_Indx04.txt.gz | s_5_1_Indx04.txt.gz |
1 | 1_PBMC_C43 | 5 | 3,4,5 | HL170 | s_3_1_Indx05.txt.gz | s_4_1_Indx05.txt.gz | s_5_1_Indx05.txt.gz |
1 | 1_PBMC_C14 | 6 | 3,4,5 | HL170 | s_3_1_Indx06.txt.gz | s_4_1_Indx06.txt.gz | s_5_1_Indx06.txt.gz |
1 | 1_PBMC_C20 | 7 | 3,4,5 | HL170 | s_3_1_Indx07.txt.gz | s_4_1_Indx07.txt.gz | s_5_1_Indx07.txt.gz |
1 | 1_PBMC_C26 | 8 | 3,4,5 | HL170 | s_3_1_Indx08.txt.gz | s_4_1_Indx08.txt.gz | s_5_1_Indx08.txt.gz |
1 | 1_PBMC_C01 | 9 | 3,4,5 | HL170 | s_3_1_Indx09.txt.gz | s_4_1_Indx09.txt.gz | s_5_1_Indx09.txt.gz |
1 | 1_PBMC_C39 | 10 | 3,4,5 | HL170 | s_3_1_Indx10.txt.gz | s_4_1_Indx10.txt.gz | s_5_1_Indx10.txt.gz |
1 | 1_PBMC_C61 | 11 | 3,4,5 | HL170 | s_3_1_Indx11.txt.gz | s_4_1_Indx11.txt.gz | s_5_1_Indx11.txt.gz |
1 | 1_PBMC_C87 | 12 | 3,4,5 | HL170 | s_3_1_Indx12.txt.gz | s_4_1_Indx12.txt.gz | s_5_1_Indx12.txt.gz |
1 | 1_PBMC_C56 | 13 | 3,4,5 | HL170 | s_3_1_Indx13.txt.gz | s_4_1_Indx13.txt.gz | s_5_1_Indx13.txt.gz |
1 | 1_PBMC_C68 | 14 | 3,4,5 | HL170 | s_3_1_Indx14.txt.gz | s_4_1_Indx14.txt.gz | s_5_1_Indx14.txt.gz |
1 | 1_PBMC_C74 | 15 | 3,4,5 | HL170 | s_3_1_Indx15.txt.gz | s_4_1_Indx15.txt.gz | s_5_1_Indx15.txt.gz |
1 | 1_PBMC_C80 | 16 | 3,4,5 | HL170 | s_3_1_Indx16.txt.gz | s_4_1_Indx16.txt.gz | s_5_1_Indx16.txt.gz |
1 | 1_PBMC_C92 | 17 | 3,4,5 | HL170 | s_3_1_Indx17.txt.gz | s_4_1_Indx17.txt.gz | s_5_1_Indx17.txt.gz |
1 | 1_PBMC_C51 | 18 | 3,4,5 | HL170 | s_3_1_Indx18.txt.gz | s_4_1_Indx18.txt.gz | s_5_1_Indx18.txt.gz |
1 | 1_PBMC_C57 | 19 | 3,4,5 | HL170 | s_3_1_Indx19.txt.gz | s_4_1_Indx19.txt.gz | s_5_1_Indx19.txt.gz |
1 | 1_PBMC_C63 | 20 | 3,4,5 | HL170 | s_3_1_Indx20.txt.gz | s_4_1_Indx20.txt.gz | s_5_1_Indx20.txt.gz |
2 | 1_PBMC_C69 | 1 | 6,7,8 | HL170 | s_6_1_Indx01.txt.gz | s_7_1_Indx01.txt.gz | s_8_1_Indx01.txt.gz |
2 | 1_PBMC_C06 | 2 | 6,7,8 | HL170 | s_6_1_Indx02.txt.gz | s_7_1_Indx02.txt.gz | s_8_1_Indx02.txt.gz |
2 | 1_PBMC_C18 | 3 | 6,7,8 | HL170 | s_6_1_Indx03.txt.gz | s_7_1_Indx03.txt.gz | s_8_1_Indx03.txt.gz |
2 | 1_PBMC_C24 | 4 | 6,7,8 | HL170 | s_6_1_Indx04.txt.gz | s_7_1_Indx04.txt.gz | s_8_1_Indx04.txt.gz |
2 | 1_PBMC_C28 | 5 | 6,7,8 | HL170 | s_6_1_Indx05.txt.gz | s_7_1_Indx05.txt.gz | s_8_1_Indx05.txt.gz |
2 | 1_PBMC_C34 | 6 | 6,7,8 | HL170 | s_6_1_Indx06.txt.gz | s_7_1_Indx06.txt.gz | s_8_1_Indx06.txt.gz |
2 | 1_PBMC_C46 | 7 | 6,7,8 | HL170 | s_6_1_Indx07.txt.gz | s_7_1_Indx07.txt.gz | s_8_1_Indx07.txt.gz |
2 | 1_PBMC_C17 | 8 | 6,7,8 | HL170 | s_6_1_Indx08.txt.gz | s_7_1_Indx08.txt.gz | s_8_1_Indx08.txt.gz |
2 | 1_PBMC_C35 | 9 | 6,7,8 | HL170 | s_6_1_Indx09.txt.gz | s_7_1_Indx09.txt.gz | s_8_1_Indx09.txt.gz |
2 | 1_PBMC_C41 | 10 | 6,7,8 | HL170 | s_6_1_Indx10.txt.gz | s_7_1_Indx10.txt.gz | s_8_1_Indx10.txt.gz |
2 | 1_PBMC_C04 | 11 | 6,7,8 | HL170 | s_6_1_Indx11.txt.gz | s_7_1_Indx11.txt.gz | s_8_1_Indx11.txt.gz |
2 | 1_PBMC_C48 | 12 | 6,7,8 | HL170 | s_6_1_Indx12.txt.gz | s_7_1_Indx12.txt.gz | s_8_1_Indx12.txt.gz |
2 | 1_PBMC_C64 | 13 | 6,7,8 | HL170 | s_6_1_Indx13.txt.gz | s_7_1_Indx13.txt.gz | s_8_1_Indx13.txt.gz |
2 | 1_PBMC_C78 | 14 | 6,7,8 | HL170 | s_6_1_Indx14.txt.gz | s_7_1_Indx14.txt.gz | s_8_1_Indx14.txt.gz |
2 | 1_PBMC_C90 | 15 | 6,7,8 | HL170 | s_6_1_Indx15.txt.gz | s_7_1_Indx15.txt.gz | s_8_1_Indx15.txt.gz |
2 | 1_PBMC_C53 | 16 | 6,7,8 | HL170 | s_6_1_Indx16.txt.gz | s_7_1_Indx16.txt.gz | s_8_1_Indx16.txt.gz |
2 | 1_PBMC_C65 | 17 | 6,7,8 | HL170 | s_6_1_Indx17.txt.gz | s_7_1_Indx17.txt.gz | s_8_1_Indx17.txt.gz |
2 | 1_PBMC_C54 | 18 | 6,7,8 | HL170 | s_6_1_Indx18.txt.gz | s_7_1_Indx18.txt.gz | s_8_1_Indx18.txt.gz |
2 | 1_PBMC_C88 | 19 | 6,7,8 | HL170 | s_6_1_Indx19.txt.gz | s_7_1_Indx19.txt.gz | s_8_1_Indx19.txt.gz |
2 | 1_PBMC_C94 | 20 | 6,7,8 | HL170 | s_6_1_Indx20.txt.gz | s_7_1_Indx20.txt.gz | s_8_1_Indx20.txt.gz |
TubeCont | CD4+ | 21 | 1 | HL170 | s_1_1_Indx21.txt.gz | ||
TubeCont | CD19+ | 22 | 1 | HL170 | s_1_1_Indx22.txt.gz | ||
TubeCont | PBMC | 23 | 1 | HL170 | s_1_1_Indx23.txt.gz |
Mapping Statistics
- TSCC Mapping:
batch_STAR_cufflink2_HTseq.pl hg19
- Mapping analysis in Genome Miner:
/home/kunzhang/RNAseq/SCAP/scripts/get_STAR_mapping_stats.pl PBMC_HL170 > PBMC_HL170_mapping_stats.txt /home/kunzhang/RNAseq/SCAP/scripts/get_STAR_TPM_matrix.pl PBMC_HL170 > PBMC_HL170_TPM.txt
- Summary:
Singular Analysis: Comparison with Neurons
- Neuron libraries: C1 huNu experiment 20140227
- Removed unannotated genes (i.e. all genes without HGNC Names)
- Singular Software 3.0 AutoAnalysis: LOD = 1; Top 100 differentially expressed genes
Principal Component Analysis:
Hierarchical Clustering:
- Can identify two potential subpoulations of PBMCs (labeled Group1 and Group2)
- Can identify three subsets of PBMC-related genes (Set1, Set2, Set3):
GeneID GroupID ' GeneID GroupID ' GeneID GroupID SMCHD1 Set1 FAM208B Set2 MAP3K1 Set3 PHC3 Set1 HIVEP2 Set2 HLA-DRA Set3 PDE7A Set1 HSP90AB1 Set2 CD74 Set3 WAC Set1 ANK3 Set2 LYN Set3 RPL3 Set1 TESPA1 Set2 ARHGAP24 Set3 STK17B Set1 ABLIM1 Set2 NEAT1 Set3 RPL30 Set1 OXNAD1 Set2 AOAH Set3 LAPTM5 Set1 CAMK4 Set2 FGR Set3 RASSF3 Set1 PRKCA Set2 MYO1F Set3 DOCK2 Set1 PDK1 Set2 RBMS1 Set3 ZBTB20 Set1 IL6ST Set2 GNAQ Set3 FYB Set1 BCL11B Set2 HIF1A-AS2 Set3 PTPRC Set1 LRRC8C Set2 ERBB2IP Set3 B2M Set1 LRRC75A Set2 PPP1R12A Set3 LRRC75A-AS1 Set2 VAPA Set3 SKP1 Set2 NCOA1 Set3 TC2N Set2 LRRFIP1 Set3 CCR7 Set2 OSBPL8 Set3 TRAC Set2 CAST Set3 PCED1B Set2 SMG7 Set3 MAML2 Set2 NCF2 Set3 CD96 Set2 C10orf11 Set3 ITK Set2 RBM47 Set3 IL7R Set2 DOCK5 Set3 LDHB Set2 LYZ Set3 CD3G Set2 VCAN Set3 CD3D Set2 CPVL Set3 LEF1 Set2 MAML3 Set3 PLXDC2 Set3 VMP1 Set3 RAP1GAP2 Set3 EVI5 Set3 ZEB2 Set3 MARCH1 Set3 JAZF1 Set3
Violin Plot
File:PBMC Neuron Violin Plot.png
- PBMC Upregulated Genes (Log2Ex Values >2fold)
ID PBMC Neuron B2M 12.06088994 0 PTPRC 11.43596383 1.246360079 MAML2 10.74831794 3.139034281 FYB 10.47348499 0 ZBTB20 10.07262771 4.365163912 IL7R 9.958356597 0 LEF1 9.924274838 0 STK17B 9.712558873 0 DOCK2 9.30727295 2.349849452 PDE7A 9.165049555 4.056165937 MAP3K1 9.135716522 2.156183693 ERBB2IP 8.885414539 4.439420173 PCED1B 8.831443091 3.733026029 VMP1 8.759459637 4.360635962 AOAH 8.70815656 2.212552957 TC2N 8.668049838 0.38107932 HLA-DRA 8.631302971 0 LDHB 8.578374713 2.815661712 CD96 8.56703784 0 ITK 8.533862961 0 RPL30 8.485380678 1.327596607 ARHGAP24 8.425139607 1.330694255 CD3G 8.383179076 0 RASSF3 8.310063349 0 CPVL 8.206916149 3.184292824 CAST 8.190390515 4.027333343 IL6ST 8.001360942 3.384831455 SKP1 7.841030974 3.52743585 VCAN 7.837267496 0.283828219 LRRC8C 7.812971223 3.532507267 RPL3 7.713171439 1.899806557 LYZ 7.670636524 0 PDK1 7.60225638 2.734495713 CD74 7.341776762 0 LYN 7.329245674 0 TRAC 7.074289051 0 LAPTM5 7.068575619 0 C10orf11 7.03026631 2.820673439 RBM47 6.9559114 0.450124234 HIF1A-AS2 6.852078227 2.774368163 NCF2 6.742711713 0 LRRC75A-AS1 6.624588689 2.261847491 CCR7 6.457177404 0 FGR 6.302947632 0 DOCK5 6.259374053 0.49461772 CD3D 6.096667723 0 LRRC75A 6.018687421 2.076496088 MYO1F 5.785705604 0.622264566
Singular Analysis: Comparison within Groups
- Comparison of putative PBMC sub-groups identified above (see PBMC Neuron Hierarchical Cluster)
- Singular 3.0: Autoanalysis: LOD1; top 100 differentially expressed genes
PCA Analysis: Group 1/2
- 3D PCA Plot
File:PBMC Group 3d PCA plot.png
Hierarchical Clustering Analysis: Group 1/2
- Note that there remains heterogeneity in these groups, but further splitting is impossible due to the low sample sizes
- Can identify 4 potential gene clusters (Set1, Set2, Set3, Set4):
GeneID GroupID ' GeneID GroupID ' GeneID GroupID ' GeneID GroupID MYBL1 Set 1 MARCH1 Set 2 RICTOR Set 3 LCLAT1 Set 4 ID2 Set 1 CD74 Set 2 STK17B Set 3 INPP4B Set 4 NASP Set 1 JAZF1 Set 2 STRBP Set 3 PPIL4 Set 4 VMP1 Set 1 SETBP1 Set 2 FAM117B Set 3 FHIT Set 4 ZFAND6 Set 1 CCDC88A Set 2 RALGPS2 Set 3 MAML2 Set 4 QKI Set 1 HDAC9 Set 2 BACH2 Set 3 OXNAD1 Set 4 AOAH Set 1 CAST Set 2 CGGBP1 Set 3 PLCL1 Set 4 FGR Set 1 SMG7 Set 2 RNF111 Set 3 BCLAF1 Set 4 ZEB2 Set 1 APLP2 Set 2 RNF2 Set 3 LRRC75A Set 4 DIAPH2 Set 2 AFF3 Set 3 IL7R Set 4 VCAN-AS1 Set 2 CYLD Set 3 TC2N Set 4 NCF2 Set 2 C1orf112 Set 3 ANK3 Set 4 IRAK3 Set 2 UBA3 Set 3 HIVEP2 Set 4 LYN Set 2 FCHSD2 Set 3 PHC3 Set 4 EVI5 Set 2 R3HDM2 Set 3 TXK Set 4 ARHGAP24 Set 2 WDFY4 Set 3 PRKCQ Set 4 RBM47 Set 2 ADAM28 Set 3 RNF169 Set 4 SLC8A1 Set 2 SFT2D1 Set 3 XRRA1 Set 4 CPVL Set 2 CASP1 Set 3 RPL3 Set 4 C10orf11 Set 2 SESTD1 Set 3 RPL35A Set 4 LYZ Set 2 HLA-DRA Set 3 RPL30 Set 4 DOCK5 Set 2 OSBPL10 Set 3 RPL5 Set 4 MAML3 Set 2 RASGRP3 Set 3 LRRC8C Set 4 VCAN Set 2 BANK1 Set 3 GNB2L1 Set 4 PLXDC2 Set 2 BLK Set 3 LDHB Set 4 MS4A1 Set 3 CD3D Set 4 BCL11A Set 3 CD3G Set 4 EBF1 Set 3 TESPA1 Set 4 CCR7 Set 4 LEF1 Set 4 CAMK4 Set 4 PRKCA Set 4
Violin Plot: Group 1/2
File:PBMC Group Violin Plot.png
- Top Genes Expressed in Group 1 versus Group 2 (log2Ex > 2):
Top Genes Group 1 | ' | ' | ' | Top Genes Group 2 | ' | ' |
ID | Group1 | Group2 | ID | Group1 | Group2 | |
LYN | 9.129954615 | 0.049282249 | LEF1 | 0.555570778 | 10.40907802 | |
OSBPL10 | 9.323622829 | 0.273157782 | CAMK4 | 0 | 9.597364962 | |
LYZ | 9.470710979 | 0.521905042 | PRKCA | 1.029187823 | 9.586852639 | |
MARCH1 | 9.335855359 | 0.622883509 | TC2N | 0 | 9.152839755 | |
SLC8A1 | 9.592184637 | 0.844184763 | LDHB | 0 | 9.06354959 | |
MS4A1 | 11.29801193 | 0 | CD3G | 0 | 8.868453579 | |
PLXDC2 | 10.31543618 | 0.963511116 | CCR7 | 0 | 6.941098092 | |
HLA-DRA | 10.43849208 | 0 | CD3D | 0 | 6.58209455 | |
ARHGAP24 | 10.23188851 | 0 | LRRC75A | 0 | 6.499326104 | |
CPVL | 10.01351303 | 0 | TESPA1 | 1.380452407 | 8.235450163 | |
ADAM28 | 9.785255259 | 0 | LCLAT1 | 1.48864354 | 7.278017747 | |
VCAN | 9.643546202 | 0 | RNF169 | 1.673443356 | 7.641024287 | |
EBF1 | 9.106720614 | 0 | ANK3 | 2.05883598 | 9.336394755 | |
BCL11A | 8.992256824 | 0 | LRRC8C | 1.883669687 | 8.291618061 | |
SESTD1 | 8.960251413 | 0 | XRRA1 | 1.796026626 | 7.766035558 | |
C10orf11 | 8.829801606 | 0 | IL7R | 2.984612134 | 10.44050025 | |
MAML3 | 8.800819433 | 0 | INPP4B | 2.818518269 | 9.434072621 | |
RBM47 | 8.756778547 | 0 | ||||
VCAN-AS1 | 8.675922641 | 0 | ||||
WDFY4 | 8.09846509 | 0.99494171 | ||||
DOCK5 | 8.063963957 | 0 | ||||
BLK | 7.816216488 | 0 | ||||
SFT2D1 | 7.233426745 | 0 | ||||
RASGRP3 | 7.055756928 | 0 | ||||
BANK1 | 10.23475098 | 1.768650147 | ||||
FGR | 8.074886707 | 1.422475224 | ||||
CD74 | 9.118670542 | 2.246347277 | ||||
IRAK3 | 8.334750938 | 2.694802207 | ||||
CASP1 | 8.932061541 | 3.062657096 | ||||
EVI5 | 9.334982725 | 3.229757099 | ||||
JAZF1 | 9.467325084 | 3.619718186 |
Bicluster Analysis: Splitting Samples into two Groups
- To try and separate out single PBMC groupings prior to Singular analysis (requires comparison of at least two data sets) without using human Neurons
- Wanted to do biclustering to generate a first level hierarchical spit of the samples as per Rui's analysis
Overdispersed genes
/home/kunzhang/RNAseq/SCAP/scripts/exprMatrix2overDispersedGenes.pl PBMC_HL170_TPM.txt > PBMC_HL170_TPM.txt_OverDisp.txt /home/kunzhang/RNAseq/SCAP/scripts/extract_gene_set_ENSG.pl PBMC_HL170_TPM.txt_OverDisp.txt PBMC_HL170_TPM.txt > PBMC_HL170_OverDisp_TPM_Matrix.txt /home/kunzhang/RNAseq/SCAP/scripts/filterExprMatrix.pl PBMC_noTC_HL170_TPM.txt > PBMC_noTC_Filtered_HL170_TPM.txt
- 28 samples
- 3096 genes
/home/kunzhang/RNAseq/SCAP/scripts/exprMatrix2overDispersedGenes.pl PBMC_noTC_Filtered_HL170_TPM.txt > PBMC_noTC_Filtered_HL170_TPM_OverDisp.txt
- 92 Over-dispersed genes
/home/kunzhang/RNAseq/SCAP/scripts/extract_gene_set_ENSG.pl PBMC_noTC_Filtered_HL170_TPM_OverDisp.txt PBMC_noTC_Filtered_HL170_TPM.txt > PBMC_HL170_Filtered_noTC_OverDisp_TPM_Matrix.txt
Hierarchical Clustering
library(gplots) x=read.table("PBMC_HL170_Filtered_noTC_OverDisp_TPM_Matrix.txt",header=TRUE,row.names=1); x.cor = cor(log10(x+1),use="pairwise.complete.obs",method="pearson") heatmap.2(as.matrix(x.cor), col=bluered(128), scale="none", cexCol=0.6, cexRow=0.6 ,key=T, symkey=F,density.info="histogram",trace="none",dendrogram="both",Rowv=TRUE,Colv=TRUE)
Cutting Cluster Dendrogram
hc.rows<- hclust(dist(x.cor)) plot(hc.rows, cex = 0.6, cex.main = 2) ct<- cutree(hc.rows, h=3.0) rect.hclust(hc.rows, h=3.0) # draw red rectangles to mark the subgroups write.table(ct, file="PBMC_cutree_2_clusters.txt", sep = "\t", row.names=TRUE, col.names=TRUE)
File:Cutree Dendrogram PBMC.png
Cluster Comparison using Singular 3.0
- AutoAnalysis using LOD1 and top 100 differentially expressed genes between BiCluster1 and BiCluster2 identified above