scEasyMode 1.0.1

Wrappers for automating single cell workflows in python

ScEasyMode: Wrappers for automating single cell workflows in Python

Features

• Multiseq correction in python using a within-barcode zscore correction
• Plotting for stacked barplots in your dataset
• Mouse cell filtering/separation from mixed dataset
• Scanpy wrapper that simplifies the workflow

Installation

Install using Pip

pip3 install scEasyMode

Install using a Conda Environment

• You may also use Conda to start an environment with ScEasyMode installed inside it. You can install conda from here.
• Firstly, clone the repository and create the environment as shown below. Then, activate the environment.

git clone https://github.com/johnnyUCSF/scEasyMode
cd scEasyMode
conda env create -f environment.yml
conda activate sceasymode_env

• Now start your Jupyter Notebook or Python shell inside the conda environment

Usage

Load the modules

from scEasyMode import mousefilter
from scEasyMode import clusterplot
from scEasyMode import pymulti
from scEasyMode import sceasy

Demultiplex your samples

import pandas as pd
from scEasyMode import pymulti

# Define parameters

len_10x=16 # Number of bases in cell barcodes
len_umi=12 # Length of UMI
len_multi=15, # Number of bases in the HTO barcodes / HashTag O

fastq_r1 = 'path/to/file'
fastq_r2 = 'path/to/file'
sample_name = 'test_demultiplexing'

cell_BC_file = 'path/to/cell_barcodes' # Counts Matrix after alignment and pre-processing
cell_bcs = pd.read_csv(cell_BC_file, sep='\t', header=None)[0].tolist()

multi_BC_file = 'path/to/barcodes' # Barcodes TSV file from 10x or Illumina
bcsmulti = pd.read_csv(multi_BC_file,sep=',',index_col=1,header=None)
bcsmulti.columns = ['multi']
bcsmulti = bcsmulti['multi'].tolist()

pymulti.pymulti(fastq_r1, fastq_r2, bcsmulti=bcsmulti, bcs10x=cell_bcs,
                len_10x=len_10x, len_multi=len_multi, len_umi=len_umi, split=True,
                hamming=True, median_only=True, sampname= sample_name,  filter_unmapped_reads=True)

# This function will output multiple graphs
# It will also store a matrix of the assigned barcodes in the 'pymulti' directory inside the working directory.
# Note that some reads are unmapped. If you want to retain them, you can do so by specifying filter_unmapped_reads=False.