GSE73211 Processing Pipeline

RNA-Seq code_examples 2 steps

Publication

iPSCORE: A Resource of 222 iPSC Lines Enabling Functional Characterization of Genetic Variation across a Variety of Cell Types.

Stem cell reports (2017) — PMID 28410642

Dataset

GSE73211

Comparing isogenic pairs of hESC and hiPSC lines reveals genetic background and reprogramming method as primary sources of transcriptional variation

Warning: Pipeline descriptions and code snippets may be inferred or AI-generated. Use them only as a starting point to guide analysis, and validate before use.

Processing Steps

Generate Jupyter Notebook
  1. 1

    Sequence reads were aligned to GRCh37.67 transcriptome using bowtie 0.12.7.

    Bowtie v0.12.7
    $ Bash example 
    # conda install -c bioconda bowtie # Note: Version 0.12.7 is very old and might not be directly available via conda; this command installs a recent Bowtie 1 version.
# bowtie -S <index_prefix> <reads.fastq> <output.sam> # Example alignment command for single-end reads. Replace placeholders with actual paths.
  2. 2

    TPM and readcount values were obtained using EMSAR v1.0

    EMSAR v1.0
    $ Bash example 
    # Installation: Clone the repository and compile.
# git clone https://github.com/zhanglab-bioinformatics/EMSAR.git
# cd EMSAR
# make

# Execution command (example for paired-end reads, adjust paths and filenames):
# ./EMSAR -r reference.fasta -1 reads_R1.fastq.gz -2 reads_R2.fastq.gz -o output_prefix
Raw Source Text 
Sequence reads were aligned to GRCh37.67 transcriptome using bowtie 0.12.7.
TPM and readcount values were obtained using EMSAR v1.0
Genome_build: GRCh37
Supplementary_files_format_and_content: tab-delimited files that contains TPM and read count information.
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