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Numrering	Referens	Omslagsbild	Hitta
1.	Mahmud, A. K. M. Firoj, et al. (författare) ProkSeq for complete analysis of RNA-Seq data from prokaryotes 2021 Ingår i: Bioinformatics. - UK : Oxford University Press. - 1367-4803 .- 1367-4811 .- 1460-2059. ; 37:1, s. 126-128 Tidskriftsartikel (refereegranskat)abstract Summary: Since its introduction, RNA-Seq technology has been used extensively in studies of pathogenic bacteria to identify and quantify differences in gene expression across multiple samples from bacteria exposed to different conditions. With some exceptions, tools for studying gene expression, determination of differential gene expression, downstream pathway analysis and normalization of data collected in extreme biological conditions is still lacking. Here, we describe ProkSeq, a user-friendly, fully automated RNA-Seq data analysis pipeline designed for prokaryotes. ProkSeq provides a wide variety of options for analysing differential expression, normalizing expression data and visualizing data and results.Availability and implementation: ProkSeq is implemented in Python and is published under the MIT source license. The pipeline is available as a Docker container https://hub.docker.com/repository/docker/snandids/prokseq-v2.0, or can be used through Anaconda: https://anaconda.org/snandiDS/prokseq. The code is available on Github: https://github.com/snandiDS/prokseq and a detailed user documentation, including a manual and tutorial can be found at https://prokseqV20.readthedocs.io.

Mahmud, A. K. M. Firoj, et al. (författare)
ProkSeq for complete analysis of RNA-Seq data from prokaryotes
2021
Ingår i: Bioinformatics. - UK : Oxford University Press. - 1367-4803 .- 1367-4811 .- 1460-2059. ; 37:1, s. 126-128
Tidskriftsartikel (refereegranskat)abstract
- Summary: Since its introduction, RNA-Seq technology has been used extensively in studies of pathogenic bacteria to identify and quantify differences in gene expression across multiple samples from bacteria exposed to different conditions. With some exceptions, tools for studying gene expression, determination of differential gene expression, downstream pathway analysis and normalization of data collected in extreme biological conditions is still lacking. Here, we describe ProkSeq, a user-friendly, fully automated RNA-Seq data analysis pipeline designed for prokaryotes. ProkSeq provides a wide variety of options for analysing differential expression, normalizing expression data and visualizing data and results.Availability and implementation: ProkSeq is implemented in Python and is published under the MIT source license. The pipeline is available as a Docker container https://hub.docker.com/repository/docker/snandids/prokseq-v2.0, or can be used through Anaconda: https://anaconda.org/snandiDS/prokseq. The code is available on Github: https://github.com/snandiDS/prokseq and a detailed user documentation, including a manual and tutorial can be found at https://prokseqV20.readthedocs.io.

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