2018
DOI: 10.21105/joss.00583
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RNAsik: A Pipeline for complete and reproducible RNA-seq analysis that runs anywhere with speed and ease

Abstract: RNA sequencing (RNA-seq) is one of many applications of high throughput sequencing, in which millions of short sequence reads, typically around 100 bases long, are produced from RNA samples with the aim of characterising entire transcriptomes. In order to analyse RNA-seq data, multiple bioinformatics tools are collected together into a pipeline, in which each tool accepts processed data from the previous tool as its input. The RNAsik pipeline streamlines processing of RNA-seq data and facilitates the productio… Show more

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Cited by 45 publications
(32 citation statements)
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“…Sequencing reads were processed using an in house pipeline consisting of sabre tools (https://github.com/ serine/sabre) and RNAsik [20]. Samples were demultiplexed with a fork of sabre tools with the commands below.…”
Section: Demultiplexing and Mappingmentioning
confidence: 99%
“…Sequencing reads were processed using an in house pipeline consisting of sabre tools (https://github.com/ serine/sabre) and RNAsik [20]. Samples were demultiplexed with a fork of sabre tools with the commands below.…”
Section: Demultiplexing and Mappingmentioning
confidence: 99%
“…Reads were assembled using Spades v3.12.0 (67) with a coverage cutoff of 10 in ‘careful’ mode. To identify variants, the filtered sequencing data was mapped back onto the assemblies using BWA (68) as implemented in RNAsik v1.5.0 (69). Both phage-sensitive (S) and phage-resistant (R) sequencing data was mapped back onto each of the genome assemblies from S and R isolates, resulting in 4 alignment files per strain pair (S on S; S on R; R on S; and R on R).…”
Section: Methodsmentioning
confidence: 99%
“…Data analysis was performed by the Monash Bioinformatics Platform (Monash University) using the P. gingivalis W83 NCBI reference sequence NC_002950.2 [26]. Raw RNAseq FASTQ files were aligned with the BWA-MEM aligner and analyzed using the RNAsik pipeline to generate raw counts [27]. Then, Degust was used for differential gene expression analysis and visualization [28].…”
Section: Differential Gene Expressionmentioning
confidence: 99%