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R package to analyze single cell in-situ sequencing (ISS) data

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# 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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R package to analyze single cell in-situ sequencing (ISS) data

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