iss_care's Introduction
# MolDia __Package description :__ R package to analyze single cell in-situ sequencing (ISS) data # Install package ```{r} install.packages("devtools") library(devtools) install_github("mashranga/MolDia") ``` # Scope of the package The scope of the package can be devided into following broad category ## General structure of MolDia object 1. __RCA_class__ : Main object definition and structure of "RCA_class" of MolDia package ## Default example data-set 1. __marker_gene__: Neuronal marker gene by group ## Read, manipulateand filter RCA ISS data ### Read data 1. __readRCA__ : Function to read RCA ISS data. THis function has different parameter, how to read and what to read. See detail in function help. 2. __ISS_rotate__ : Rotate a tissue by specific angle or flip by x or y axis. ### Filter data 1. __RCA_barplot__: Plot bar plot on RCA data bsed on different condition. In general filter data set based on different gese condition. 1. __RCA_filter__: Filter RCA data based on poisson distibution (Experimental) ### Region of interest 1. __RCA_GridSelect__: Draw and Select grid of interest from a tissue ## ISS data summary and vizualization 1. __genesSummary__: Summary of Specific gene of interest in ISS data. This include percentage of gene of interest positive cell with their distribution in other positive cells and visa-versa. 2. __readsSummary__: Summary of RCA data 2. __ISS_pieplot__: Venn-pie chart on ISS data based on genes of interest 3. __RCA_map__: Map ISS data based on different feature like cell, gene, cluster, tSNE ## Multiple ISS data comparision 1. __ISS_compare__: Relation of multiple ISS data interms of total reads per gene. The result is presented in fitted regression line with R^2. 2. __ISS_ratiocor__: Calculate and plot correlation and ratio of total reads between genes by concedering group of tissue. ## ISS data dimention reduction 1. __RCA_tsne__: Any data in class RCA_class clusteded or not clustered used to reduce dimention to 2D by RCA-tsne. ## ISS data preprocessing 1. __RCA_preprocess__: Pre-process RCA data interms of normalization, scalling and centering ## ISS clustering ### Cluster 1. __RCA_cluster__: Cluster in-situ RCA data by different methods 2. __RCA_ClusterSelect__ : Select cluster of interest after clustering 3. __RCA_spatial__ : ISS spatial clustering (Experimental) ### Cluster marker 1. __RCA_marker__: Find Cluster marker of in-situ RCA data and plot significant gene cluster wise by barplot and heatmap. ### Cluster compare 1. __RCA_clustcompare__: Compare cluster of two tissue and find their similarity by Random forest algorithm. ## Differentially express gene 1. __RCA_DE__: Find differentially express gene by different methods ## Need to updrade 1. In function RCA_map plot empty cells foe specific genes. 2. legend problem In function RCA_map plot 3. Add violon plot in function RCA_map 4. Add tsne subplot for selected gene
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