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====Round 2==== =====K-mean cluster 1 (mostly GAD1-/GAD2- neurons)===== ../scripts/exprMatrix2overDispersedGenes.pl 2014_1st_Quater_18_expr_matrix_Z1_k-mean2_c1.txt 1 > 2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes.txt ../scripts/extract_gene_set_ENSG.pl 2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes.txt 2014_1st_Quater_18_1N_expr_matrix_filtered.txt > 2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes_expr_matrix.txt library(gplots) x=read.table("2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes_expr_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=0.1, cexRow=0.1 ,key=T, symkey=F,density.info="histogram",trace="none",dendrogram="both",Rowv=TRUE,Colv=TRUE) [[Image:2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes_sample_clustering.png|400px]] hc.rows<- hclust(dist(x.cor)) plot(hc.rows,cex=0.1) ct<- cutree(hc.rows, h=8) # rect.hclust(hc.rows, h=8) # draw red rectangles to mark the subgroups write.table(ct, file="2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes_cutree_2_clusters.txt", sep = "\t", row.names=TRUE, col.names=TRUE) [[Image:2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes_sample_clustering_cutree2.png|600px]] library(cluster) library(fpc) x[is.na(x)] <- 0 y=log10(x+1) tys = scale(t(y)) k_5=kmeans(tys, 5) k_4=kmeans(tys, 4) k_3=kmeans(tys, 3) k_2=kmeans(tys, 2) plotcluster(tys,k_2$cluster) plotcluster(tys,k_3$cluster) plotcluster(tys,k_4$cluster) plotcluster(tys,k_5$cluster) write.table(k_3$cluster, file="2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes_k-mean_3_clusters.txt", sep = "\t", row.names=TRUE, col.names=TRUE) write.table(k_2$cluster, file="2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes_k-mean_2_clusters.txt", sep = "\t", row.names=TRUE, col.names=TRUE) [[Image:2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes_k2_clusters.png|300px]][[Image:2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes_k3_clusters.png|300px]] [[Image:2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes_k4_clusters.png|300px]][[Image:2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes_k5_clusters.png|300px]] *It appeared that these neurons can be divided into four cleanly separated clusters. The next questions would be to find out the identity or meaning of these clusters. =====Finding genes up-regulated in the four sub-groups of K-mean cluster 1===== *For this I took the over-dispersed genes in all k-mean (k=2) cluster 1 samples from Round 1 (2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes_expr_matrix.txt), label the samples with four groups based on the Round 2 k-mean clustering results (2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes_k-mean_4_clusters), and run the SAM analysis under the multi-class model. Obviously most of the genes (365/486) are differentially expressed in one or more groups. I sorted these genes based on the "contrast" for each of the four groups, then selected the top 10 genes that have the highest contrast for each group (note that I skipped a few that have no annotations, such as RP11-123O10.4). [[Media:2014_1st_Quater_18_k-mean2_c1_Z1_overDispersed_genes_expr_matrix_for_SAM_4-clusters.xlsx]] Cluster c1.1 {| {{table}} | align="center" style="background:#f0f0f0;"|'''HUGO''' | align="center" style="background:#f0f0f0;"|'''contrast-1''' | align="center" style="background:#f0f0f0;"|'''contrast-2''' | align="center" style="background:#f0f0f0;"|'''contrast-3''' | align="center" style="background:#f0f0f0;"|'''contrast-4''' |- | KCNIP3||11.16739647||-4.478728361||-2.350967986||-8.986883423 |- | PTPRK||10.01585583||-8.448597715||3.281430094||-10.8506507 |- | EGR1||9.747299154||-4.684003738||-1.824346768||-7.36895931 |- | LINGO1||9.58144463||-4.624228762||-0.40094134||-9.099549439 |- | HECW1||9.394975421||-5.855567107||-1.766355741||-5.738812994 |- | SEMA4D||8.81652661||-2.666120885||-2.904782293||-6.55968048 |- | NGEF||8.802471142||-4.446578057||1.310832307||-10.42218722 |- | ZNF804B||8.5895529||-6.751014558||-0.494902477||-5.345801831 |- | RORB||8.54586603||-3.975389056||-2.334804946||-5.602362517 |- | CPNE4||8.480061688||-3.478772801||-1.500439455||-7.129478032 |- | |} Cluster c1.2 {| {{table}} | align="center" style="background:#f0f0f0;"|'''HUGO''' | align="center" style="background:#f0f0f0;"|'''contrast-1''' | align="center" style="background:#f0f0f0;"|'''contrast-2''' | align="center" style="background:#f0f0f0;"|'''contrast-3''' | align="center" style="background:#f0f0f0;"|'''contrast-4''' |- | EYA4||-5.321417894||12.84154833||-6.951889857||4.354034676 |- | PID1||-4.831615771||12.56961797||-5.8966099||2.475220629 |- | PHKB||-4.678402329||12.53723223||-6.323235779||2.853976955 |- | SEC14L1||-4.063798258||12.32036809||-6.629922109||2.568378636 |- | PDE3A||-3.022438352||12.1453072||-9.026753944||4.419686124 |- | HFM1||-4.719507944||12.04260411||-5.660492381||2.521496057 |- | PPEF2||-3.137958388||12.00043463||-7.707046659||2.960175498 |- | SLCO5A1||-3.904449914||11.97087414||-6.695142422||2.771008518 |- | GRIP1||-3.072843559||8.984872116||-12.26343691||12.04528531 |- | FSTL5||-0.971506882||8.634044019||-7.959248851||3.462288967 |- | |} Cluster c1.3 {| {{table}} | align="center" style="background:#f0f0f0;"|'''HUGO''' | align="center" style="background:#f0f0f0;"|'''contrast-1''' | align="center" style="background:#f0f0f0;"|'''contrast-2''' | align="center" style="background:#f0f0f0;"|'''contrast-3''' | align="center" style="background:#f0f0f0;"|'''contrast-4''' |- | XIST||-7.68079175||-2.540266439||12.60231218||-2.948850821 |- | SYN3||4.509683673||-7.724417995||8.033069861||-9.762531396 |- | STXBP5L||6.297609932||-8.539816682||7.94343846||-11.4885019 |- | CBLN2||7.536329826||-9.613307235||7.650603365||-11.86021 |- | CA10||7.632543482||-10.16386485||7.578192948||-11.35073153 |- | FAM19A1||7.740036874||-9.88390345||7.393307367||-11.54462373 |- | TESPA1||8.398699091||-10.48531557||7.16022654||-11.60713383 |- | DGKB||5.667978001||-6.42129736||7.073847338||-11.51450378 |- | ANKDD1A||-3.551719544||-0.094358135||6.717202522||-3.652511861 |- | SLIT3||4.749934938||-6.512804085||6.654470337||-9.486357108 |- | |} Cluster c1.4 {| {{table}} | align="center" style="background:#f0f0f0;"|'''HUGO''' | align="center" style="background:#f0f0f0;"|'''contrast-1''' | align="center" style="background:#f0f0f0;"|'''contrast-2''' | align="center" style="background:#f0f0f0;"|'''contrast-3''' | align="center" style="background:#f0f0f0;"|'''contrast-4''' |- | ERBB4||-5.47746011||6.466422889||-8.491198974||13.09425661 |- | ZNF385D||-5.612887639||6.706045987||-8.288955267||12.78215485 |- | GAD1||-3.992672286||7.380574545||-10.18753447||12.2404974 |- | GRIP1||-3.072843559||8.984872116||-12.26343691||12.04528531 |- | GAD2||-4.399414548||6.847386992||-9.173866991||12.02002257 |- | KLHL5||-2.873803987||3.718134302||-8.032442931||11.36189782 |- | SLC6A1||-3.64699617||8.167746887||-10.4614637||11.29912374 |- | QKI||-3.926567386||5.118752239||-7.596491468||10.93301198 |- | SAMD5||-1.299998198||2.202125809||-8.017337836||10.52149593 |- | TENM3||-1.967305855||1.641470543||-6.793668393||10.43483179 |- | |} *Now I combined all the "top-ten" differentially expressed genes that I found between Cluster 1/2 and four sub-clusters in 1, and compiled a "[[Media:2014_1st_Quater_18_1N_cluster_specific_genes.txt|cluster-specific gene list]]". With this list, I made a heat map for the expression levels of these genes across all samples. [[Image:2014_1st_Quater_18_1N_cluster_specific_genes_expr_heatmap.png|800px]]
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