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An open API service providing mapping between scientific papers and software projects that are mentioned in them.

Papers: 10.1186/s13293-020-00335-2

https://doi.org/10.1186/s13293-020-00335-2

Investigating transcriptome-wide sex dimorphism by multi-level analysis of single-cell RNA sequencing data in ten mouse cell types

Cited by: 18
Author(s): Tianyuan Lu, Jessica C. Mar
Published: over 4 years ago

Software Mentions 4

bioconductor: GSVA
Gene Set Variation Analysis for microarray and RNA-seq data
Papers that mentioned: 893
Very Likely Science (100)
bioconductor: scDD
Mixture modeling of single-cell RNA-seq data to identify genes with differential distributions
Papers that mentioned: 16
Very Likely Science (100)
cran: Seurat
Tools for Single Cell Genomics
Papers that mentioned: 1,512
Very Likely Science (100)
pypi: GSVA
Python CLI and module for running the GSVA R bioconductor package with Python Pandas inputs and outputs.
Papers that mentioned: 893
Very Likely Science (100)