List of custom script plugins for analysis

Ajit Johnson Nirmal

R

Use these scripts by:

library(devtools)
library(roxygen2)
source_url ("")

Merge multiple transcripts into one gene

source_url("https://raw.githubusercontent.com/ajitjohnson/Jupyter-Notebooks/master/r_scripts/collapse_to_one_gene.R")
genesummary (x)

After normalization, this function can be used to plot the before & after comparision (barplot)

source_url("https://raw.githubusercontent.com/ajitjohnson/Jupyter-Notebooks/master/r_scripts/plot_before_after_normalization.R")
plotba (x,y)

Go enrichment analysis

Requires output from a DESeq analysis with a column name "padj"

source_url("https://raw.githubusercontent.com/ajitjohnson/Jupyter-Notebooks/master/r_scripts/goenrichment.R")
goenrichment (x)

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Python

Use these scripts by:

Run file_url and then run the following command

import wget
exec(open(wget.download(file_url)).read())

Preprocess CycIF data: Clean Data

Requires a pandas dataframe with cells on rows and markers/genes on columns.

file_url = 'https://raw.githubusercontent.com/ajitjohnson/Jupyter-Notebooks/master/py_scripts/mi_pp_cleandata.py'
exec(open(wget.download(file_url)).read())
mi_pp_cleandata (x)

Preprocess CycIF data: Normalization

Requires a pandas dataframe with cells on rows and markers/genes on columns.

file_url = 'https://raw.githubusercontent.com/ajitjohnson/Jupyter-Notebooks/master/py_scripts/mi_pp_normalize.py'
exec(open(wget.download(file_url)).read())
mi_pp_normalize (x)

Preprocess CycIF data: Convert dataframe into AnnData (Annotated Data)

Requires a pandas dataframe with cells on rows and markers/genes on columns.

file_url = 'https://raw.githubusercontent.com/ajitjohnson/Jupyter-Notebooks/master/py_scripts/mi_pp_anndata.py'
exec(open(wget.download(file_url)).read())
mi_pp_anndata (x)