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

Papers: 10.15252/msb.20188339

https://doi.org/10.15252/msb.20188339

Linking aberrant chromatin features in chronic lymphocytic leukemia to transcription factor networks

Cited by: 31
Author(s): Jan‐Philipp Mallm, Murat Iskar, Naveed Ishaque, Lara Klett, Sabrina J. Kugler, Jose M. Muiño, Vladimir B. Teif, Alexandra M Poos, Sebastian Großmann, Fabian Erdel, Daniele Tavernari, Sandra D. Koser, Sabrina Schumacher, Benedikt Brors, Rainer König, Daniel Remondini, Martin Vingron, Stephan Stilgenbauer, Peter Lichter, Marc Zapatka, Daniel Mertens, Karsten Rippe
Published: over 6 years ago

Software Mentions 10

bioconductor: chromVAR
Chromatin Variation Across Regions
Papers that mentioned: 46
Very Likely Science (65)
bioconductor: DESeq2
Differential gene expression analysis based on the negative binomial distribution
Papers that mentioned: 9,583
Very Likely Science (100)
bioconductor: DiffBind
Differential Binding Analysis of ChIP-Seq Peak Data
Papers that mentioned: 217
Very Likely Science (100)
bioconductor: DSS
Dispersion shrinkage for sequencing data
Papers that mentioned: 288
Very Likely Science (91)
bioconductor: edgeR
Empirical Analysis of Digital Gene Expression Data in R
Papers that mentioned: 6,568
Very Likely Science (100)
cran: ROSE
Random Over-Sampling Examples
Papers that mentioned: 131
Very Likely Science (75)
cran: STAR
Spike Train Analysis with R
Papers that mentioned: 5,759
Very Likely Science (100)
pypi: bowtie
Interactive Dashboard Toolkit.
Papers that mentioned: 1,566
Very Likely Science (90)
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: MACS2
Model Based Analysis for ChIP-Seq data
Papers that mentioned: 1,203
Very Likely Science (100)