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Blue:RNA-Seq Analyses:C1 hNuc 1000 Dataset: Protocol Optimizations
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==Average cDNA Yields Across Runs== [[File:20_C1_Runs_cDNA_Yields_2.png | 500px]] *Circled experiments represent the same batch of nuclei. There is little effect of freezing the nuclei in 10%DMSO or running the nuclei on a small chip rather than the medium chip. Global levels of cDNA were reduced with adding a nuclei stain/wash step to the loading protocol using the DNA Seq Cell Wash buffer. Also, addition of PolydIdC did globally increase cDNA levels even for the 0_Nuc conditions. *Examination of [http://genome-tech.ucsd.edu/LabNotes/index.php/Rui:LabNotes/SingleCell/2014-7-3#Basic_mapping_statistics basic mapping stats] shows that the small chip run 19 was highly variable (likely due to capture of small low RNA containing nuclei), while addition of PolydIdC seemed to stabilize mapping rates. Also, even though the cDNA yields were very high for the 0_Nuc with PolydIdC, most of the reads still mapped to ERCC. ==Comparison of C1 Run Variations on the Same Nuclei Batch== *Using Rui's mapped TPM data (unfiltered sample set), performed analysis using Fluidigmn's Singular software (v3.0.3): **[[Blue:RNA-Seq Analyses:C1 hNuc 1000 Dataset:IdentifyOutliers | Identified outliers]] based on log2 mapping rates and trimmed genes with TPM less than 2 (LOD1) **Ran Auto Analysis for top 100 differentially expressed genes ***Performed pairwise comparison of this dataset: ***Performed PCA analysis for this dataset: [[File:0227_Nuc_Pairwise_2.png | 600px]] [[File:0227_Nuc_PCA_2.png |600px]] *Can see that none of the conditions significantly affected the gene expression profiles (using top 100 differentially expressed genes) of the captured nuclei and these nuclei retained similar PCA distributions across conditions ==Analysis of Small Nuclei== *Experiment 03042014 involved NeuN-low stained nuclei that were small in size and captured using a small chip. *cDNA Yields (above) were very low for these single nuclei **Hierarchical cluster analysis using Singular Software showed that these small nuclei (pink icon on left side) group together and express interneuron genes: **PCA analysis of these small nuclei show them clustering together with other interneurons: [[File:Small_Nuclei_Analysis_HC_1.png|600px]] [[File:Small_Nuclei_Analysis_PCA_1.png|600px]] *Therefore, it appears that interneurons show smaller nuclei and lower levels of RNA compared to projection neurons. ==Analysis of Glycerol Freezing== *See Small nuclei analysis above. Included in this are 0320 (fresh) and 0321 (Glycerol Frozen) samples. As can be seen, there are no real deviations of these samples from the rest of the batches analysed, indicating that glycerol freezing at -20C overnight had little appreciable effect on the efficiency of the RNA-seq reaction. **Pairwise analysis of samples shown in Small Nuclei Analysis above: [[File:Small_Nuclei_Analysis_pairwise_1.png|600px]] *Can see very high correlation between fresh (0320) and glycerol frozen (0321) based on the top 100 differentially expressed genes ==Analyses of Gene Clusters== '''Layer1 Analysis: Interneuron Specific Genes''' *Top 27 genes based on [http://genome-tech.ucsd.edu/LabNotes/index.php/Rui:LabNotes/SingleCell/2014-7-4#DEx_genes_based_on_sample_clustering Rui's] first layer of sample clustering: **Addition of gene information and associated references [[File:Gene_Clustering_Analyses_Round_1_Top_27.xlsx]]
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