TSSer statistics

info info

Citations per year

Number of citations per year for the bioinformatics software tool TSSer

Tool usage distribution map

info info

Associated diseases


Popular tool citations

chevron_left Data analysis chevron_right
Want to access the full stats & trends on this tool?

TSSer specifications


Unique identifier OMICS_02191
Name TSSer
Software type Pipeline/Workflow
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Version 1.0
Stability Stable
Maintained No


No version available



This tool is not available anymore.

Publication for TSSer

TSSer citations


Nucleotide patterns aiding in prediction of eukaryotic promoters

PLoS One
PMCID: 5687710
PMID: 29141011
DOI: 10.1371/journal.pone.0187243

[…] t decade, several improvements in the promoter prediction process were made. Troukhan [] combined positional frequency of 5′ EST matches onto genomic DNA with the gene models. This approach, known as TSSer, is, in a nutshell, a deterministic method that predicts one transcription start site per locus. For Arabidopsis thaliana promoters, it achieves remarkable accuracy. However, even the most relia […]


ReadXplorer 2—detailed read mapping analysis and visualization from one single source

PMCID: 5167064
PMID: 27540267
DOI: 10.1093/bioinformatics/btw541

[…] ill common practice to exclude reads mapping to more than a single position from downstream analyses () and many read mapping analysis tools do not address multiple mapped reads (e.g. TSSPredator (), TSSer () and TSSAR () for TSS detection or VarScan 2 [() for single nucleotide polymorphism (SNP) detection]. For the latter tools, we assume that they incorporate all reads present in the data set pr […]


Toward high resolution population genomics using archaeological samples

PMCID: 4991838
PMID: 27436340
DOI: 10.1093/dnares/dsw029

[…] reads near the TSS of active genes would be lower than at silent genes. Based on read density at known TSSs and DHSs from the ENCODE project and using de novo methods of TSS prediction (e.g. NPEST or TSSer), it is possible to sort TSSs according to transcriptional activity of corresponding genes. In the near future, it may be feasible to quantitatively reconstruct gene expression patterns of ancie […]


Transcriptome landscape of Lactococcus lactis reveals many novel RNAs including a small regulatory RNA involved in carbon uptake and metabolism

RNA Biol
PMCID: 4829306
PMID: 26950529
DOI: 10.1080/15476286.2016.1146855

[…] RNA-seq data of TEX-treated and untreated samples was used for automated TSS calling by TSSer, using default parameters. Predicted TSSs were used to perform a MEME search to identify promoter motifs and Shine-Delgarno sequences in the regions −50 to −1 upstream of all TSSs using a zero o […]


GC3 biology in corn, rice, sorghum and other grasses

BMC Genomics
PMCID: 2895627
PMID: 20470436
DOI: 10.1186/1471-2164-11-308

[…] ut full-length cDNA support we obtained a final set of 16,497 genes. Rice promoter sequences were downloaded from the Osiris database []; positions of Transcription Start Sites were refined using the TSSer algorithm []. Rice microarray data were obtained from NCBI, Gene Expression Omnibus, platform GPL2025. We used two measures of expression: average intensity and standard deviation across 106 ser […]


Insights into corn genes derived from large scale cDNA sequencing

Plant Mol Biol
PMCID: 2709227
PMID: 18937034
DOI: 10.1007/s11103-008-9415-4

[…] CG-skew at the TSS of several eukaryotic genomes was reported by Fujimori et al. (). Using our collection of 5′ EST for corn and genomic DNA from GenBank and TIGR, we predicted TSSs for corn with the TSSer algorithm (see Methods). We have computed the CG-skew plot for 5,200 promoters having at least four supporting 5′ ESTs as evidence. Figure  shows the skew present in corn promoters which is simi […]

Want to access the full list of citations?
TSSer institution(s)
Computational and Systems Biology, Biozentrum, University of Basel, Basel, Switzerland
TSSer funding source(s)
Supported by the University of Basel and the Swiss National Science Foundation (grant number 31003A_147013).

TSSer review

star_border star_border star_border star_border star_border
star star star star star

Amr Galal

star_border star_border star_border star_border star_border
star star star star star
TSSer was a revolution in TSS automate detection and used very good statistical hypothesis but existing of new tools more powerful could give better results