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Single Cell RNASeq Data Analysis

This project focuses on analysing the single cell RNASEq data using python. FastQC package used for Quality check. Kallisto|Busttols used for Pseudo Alignment, Quantification and generating count matrices.

Data

Data has been taken from the paper "Phenotype molding of stromal cells in the lung tumor microenvironment" (https://www.nature.com/articles/s41591-018-0096-5.pdf). The paper presents a 52,698 cell catalog of TME Transcriptome in human lung tumor at single cell resolution. Data can be downloaded from https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-6149/samples/?s_page=1&s_pagesize=100 Analysing only 2 samples from patient 3

Analysis

  1. The text file focuses on the steps to convert the raw data to count matrices.
  2. The jupyter notebook focuses on the further downstream analysis.

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Single Cell RNASeq Analysis using Python

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