Sushi.R statistics

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Citations per year

Number of citations per year for the bioinformatics software tool Sushi.R

Tool usage distribution map

This map represents all the scientific publications referring to Sushi.R per scientific context
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Sushi.R specifications


Unique identifier OMICS_09832
Name Sushi.R
Alternative name Sushi
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
Computer skills Advanced
Version 1.18.0
Stability Stable
graphics, grDevices, R(>=2.10), biomaRt, zoo
Maintained Yes




No version available



  • person_outline Douglas H. Phanstiel

Publication for Sushi.R

Sushi.R citations


Chromatin immunoprecipitation (ChIP) method for non model fruit flies (Diptera: Tephritidae) and evidence of histone modifications

PLoS One
PMCID: 5854383
PMID: 29543899
DOI: 10.1371/journal.pone.0194420

[…] ence genome. After performing read alignment and, peak calling was carried out using MACS2 software, and genomic regions displaying enrichment for specific histone proteins were visualised using the ‘Sushi.R’ R/Bioconductor package []. Example peak data for histone proteins H3K4me3, H3K27Ac, H3K36me1 and H3K36me3 are presented in , which evidences histone modification in various genomic regions of […]


Transcriptome Analysis Identifies a 140 kb Region of Chromosome 3B Containing Genes Specific to Fusarium Head Blight Resistance in Wheat

Int J Mol Sci
PMCID: 5877713
PMID: 29538315
DOI: 10.3390/ijms19030852

[…] ples were filtered. Then edgeR [] were used to calculate the RPKM value (RPKM represents reads per kilobase and per million) according to the abundance data for each gene in the 12 samples. R package Sushi [] was used to explore the gene expression distribution on chromosome physical maps. […]


Using regulatory genomics data to interpret the function of disease variants and prioritise genes from expression studies

PMCID: 5850119
PMID: 29568492
DOI: 10.5256/f1000research.14748.r30355

[…] nomic locations to genes. While options for the visualisations of genomic data and interactions are outside the scope of this workflow, at least three good alternatives exist in Bioconductor: ggbio , Sushi and Gviz coupled with the GenomicInteractions package . We refer the reader to these publications and package vignettes for examples.As the sample size and power of GWASs and gene expression s […]


Ensemble genomic analysis in human lung tissue identifies novel genes for chronic obstructive pulmonary disease

Hum Genomics
PMCID: 5769240
PMID: 29335020
DOI: 10.1186/s40246-018-0132-z

[…] The R package Sushi [] was used with gene annotation and regulatory information from Ensemble BioMart [] (CTCF Binding Site, TF binding site, Open chromatin, Promoter and Enhancer information produced from ENCODE, […]


RNA dependent RNA targeting by CRISPR Cas9

PMCID: 5796797
PMID: 29303478
DOI: 10.7554/eLife.32724.036

[…] nificantly enriched guides were defined as those with an FDR-corrected p-value<0.05. Guides with a positive fold-change compared to the control were mapped to the MS2 genome and visualized using the ‘Sushi’ package (). To examine for nucleotide composition bias, sequences of guides with a significant positive enrichment were aligned at the 3´ end (PAM-proximal) and motifs were analyzed using the W […]


Topological organization and dynamic regulation of human tRNA genes during macrophage differentiation

Genome Biol
PMCID: 5607496
PMID: 28931413
DOI: 10.1186/s13059-017-1310-3

[…] generated using the deeptools computeMatrix tool with specified distances from strand-oriented tRNA genes [, ]. Signal track visualization and in situ Hi-C integration plots were generated using the Sushi package for genomic visualization []. Genome-wide tRNA gene circle visualization plots were generated using the RCircos package for Circos 2D track plots []. tDNA interactome network maps were g […]

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Sushi.R institution(s)
Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
Sushi.R funding source(s)
This project is funded by NIH grant U54HG006996 and K99HG007356 and a Damon Runyon fellow supported by the Damon Runyon Cancer Research Foundation (DRG-2122-12).

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