GSE143437 Processing Pipeline

RNA-Seq code_examples 7 steps

Publication

Zfp697 is an RNA-binding protein that regulates skeletal muscle inflammation and remodeling.

Proceedings of the National Academy of Sciences of the United States of America (2024) — PMID 39141348

Dataset

GSE143437

Single-cell transcriptomic atlas of the mouse regenerating muscle tissue

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

    Libraries were sequenced on Illumina NextSeq 500 using paired-end 26 + 8 + 58 (according to 10X Chromium Single Cell 3' protocol)

    scRNA-seq
  2. 2

    Sequences were aligned to mm10 using Cell Ranger v2 pipeline (10X Genomics)

    Cell Ranger
  3. 3

    Gene expression data was processed with Seurat v2.3.4 (Satija lab) using R v3.6.2 (2019-12-12)

    Seurat v2.3.4
  4. 4

    Initial data filtering (minimum cells to express an included gene = 3, minium genes to be expressed in an included cell = 200)

  5. 5

    Filtering by percent mitochondiral genes in included cells (maximum 0.2), number of UMIs in included cells (minimum 1000, maximum 60000), and number of mapped genes in included cells (maximum 8000)

  6. 6

    Log-normalization of expression data

  7. 7

    Cell annotations in metadata derived from unsupervised clustering in CCA space (CCA coefficients obtained by MultiCCA from Seurat (Satija Lab).

    Seurat

Tools Used

scRNA-seq
Raw Source Text 
Libraries were sequenced on Illumina NextSeq 500 using paired-end 26 + 8 + 58 (according to 10X Chromium Single Cell 3' protocol)
Sequences were aligned to mm10 using Cell Ranger v2 pipeline (10X Genomics)
Gene expression data was processed with Seurat v2.3.4 (Satija lab) using R  v3.6.2 (2019-12-12)
Initial data filtering (minimum cells to express an included gene = 3, minium genes to be expressed in an included cell = 200)
Filtering by percent mitochondiral genes in included cells (maximum 0.2), number of UMIs in included cells (minimum 1000, maximum 60000), and number of mapped genes in included cells (maximum 8000)
Log-normalization of expression data
Cell annotations in metadata derived from unsupervised clustering in CCA space (CCA coefficients obtained by MultiCCA from Seurat (Satija Lab).
Genome_build: mm10
Supplementary_files_format_and_content: .txt tabulated files of metadata information, normalized gene expression matrix, and raw gene expression matrix
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