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

Papers: 10.1186/s13059-021-02337-8

https://doi.org/10.1186/s13059-021-02337-8

Best practices on the differential expression analysis of multi-species RNA-seq

Cited by: 36
Author(s): Matthew Chung, Vincent M. Bruno, David A. Rasko, Christina A. Cuomo, José F. Muñoz, Jonathan Livny, Amol Shetty, Anup Mahurkar, Julie C. Dunning Hotopp
Published: about 4 years ago

Software Mentions 10

bioconductor: DESeq2
Differential gene expression analysis based on the negative binomial distribution
Papers that mentioned: 9,583
Very Likely Science (100)
bioconductor: edgeR
Empirical Analysis of Digital Gene Expression Data in R
Papers that mentioned: 6,568
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bioconductor: limma
Linear Models for Microarray Data
Papers that mentioned: 7,776
Very Likely Science (78)
cran: STAR
Spike Train Analysis with R
Papers that mentioned: 5,759
Very Likely Science (100)
cran: vegan
Community Ecology Package
Papers that mentioned: 6,903
Very Likely Science (100)
cran: WGCNA
Weighted Correlation Network Analysis
Papers that mentioned: 3,479
Very Likely Science (85)
pypi: HTSeq
A framework to process and analyze data from high-throughput sequencing (HTS) assays
Papers that mentioned: 3,071
Very Likely Science (65)
pypi: kallisto
The Kallisto software enables the efficient calculation of atomic features that can be used within a quantitative structure-activity relationship (QSAR) approach. Furthermore, several modelling helpers are implemented.
Papers that mentioned: 307
Very Likely Science (100)
pypi: MetaPhlAn
MetaPhlAn is a computational tool for profiling the composition of microbial communities (Bacteria, Archaea and Eukaryotes) from metagenomic shotgun sequencing data (i.e. not 16S) with species-level. With the newly added StrainPhlAn module, it is now possible to perform accurate strain-level microbial profiling.
Papers that mentioned: 306
Very Likely Science (100)
pypi: sleuth
Papers that mentioned: 59
Very Likely Science (65)