Salmon-Easy: An alignment-free RNA-seq quantitative strategy based on partial genome indexing
Pages 55 - 64
Abstract
In recent years, transcriptome sequencing has been widely used in biological gene expression analysis, mutation analysis and many other aspects. The current second-generation high-throughput RNA sequencing raw data analysis methods have disadvantages such as high requirements for platform hardware, long time, and preference for analyzing species. Based on the comparison tool Salmon, we expanded its local genome indexing strategy and comparison method and established a second-generation RNA sequencing analysis process Salmon-easy. This method uses easily accessible genome sequence files and genome annotation files to effectively index part of the genome. In the process of processing the original sequencing data, the hardware occupancy is reduced, and the processing speed is increased. At the same time, comparing with the traditional method STAR based on alignment (Alignment-based) and Salmon based on CDS area index, it is found that Salmon-easy is more accurate and convenient. Therefore, the establishment of Salmon-easy provides a new idea for the analysis of the original data of second-generation RNA sequencing on low-configuration platforms.
References
[1]
WANG Z, GERSTEIN M, SNYDER M. 2009. RNA-Seq: a revolutionary tool for transcriptomics [J]. Nature reviews Genetics. 10(1): 57-63.
[2]
THIND A, MONGA I, THAKUR P, 2021. Demystifying emerging bulk RNA-Seq applications: the application and utility of bioinformatic methodology [J]. Briefings in bioinformatics. 22(6).
[3]
LI H, HANDSAKER B, WYSOKER A, 2009. The Sequence Alignment/Map format and SAMtools [J]. Bioinformatics (Oxford, England). 25(16): 2078-9.
[4]
LEE C, MARAGKAKIS M. 2021. SamQL: a structured query language and filtering tool for the SAM/BAM file format [J]. BMC bioinformatics.22(1): 474.
[5]
YU X, LIU X. 2020 Mapping RNA-seq reads to transcriptomes efficiently based on learning to hash method [J]. Computers in biology and medicine. 116: 103539.
[6]
DANECEK P, BONFIELD J, LIDDLE J, 2021 Twelve years of SAMtools and BCFtools [J]. GigaScience. 10(2).
[7]
PATRO R, MOUNT S, KINGSFORD C. 2014. Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms [J]. Nature biotechnology.32(5): 462-4.
[8]
LIAO Y, SMYTH G, SHI W. 2014. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features [J]. Bioinformatics (Oxford, England). 30(7): 923-30.
[9]
KOLDE R. 2019. pheatmap: Pretty Heatmaps [J].
[10]
MURTAGH F, LEGENDRE P. 2014. Ward's Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward's Criterion? [J]. Journal of Classification. 31(3): 274-95.
[11]
WICKHAM H. 2016. ggplot2: Elegant Graphics for Data Analysis [M].
[12]
PERTEA G, PERTEA M. 2020,9. GFF Utilities: GffRead and GffCompare [J]. F1000Research.
[13]
CAREY M L A R G A V. 2009. rtracklayer: an R package for interfacing with genome browsers [J]. Bioinformatics (Oxford, England). 25: 1841-2.
[14]
ROBINSON CSAMILAMD. 2015. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences [J]. F1000Research. 4(1521).
[15]
[DOBIN A, DAVIS C, SCHLESINGER F, 2013. STAR: ultrafast universal RNA-seq aligner [J]. Bioinformatics (Oxford, England). 29(1): 15-21.
[16]
KASSAMBARA A, HERVIOU L, OVEJERO S, 2021. RNA-sequencing data-driven dissection of human plasma cell differentiation reveals new potential transcription regulators [J]. Leukemia. 35(5): 1451-62.
[17]
EWELS P, MAGNUSSON M, LUNDIN S, 2016. MultiQC: summarize analysis results for multiple tools and samples in a single report [J]. Bioinformatics. 32(19): 3047-8.
[18]
CHEN S, ZHOU Y, CHEN Y, 2018. fastp: an ultra-fast all-in-one FASTQ preprocessor [J]. Bioinformatics (Oxford, England). 34(17): i884-i90.
[19]
OKI T, MERCIER F, KATO H, 2021. Imaging dynamic mTORC1 pathway activity in vivo reveals marked shifts that support time-specific inhibitor therapy in AML [J]. Nature communications. 12(1): 245.
[20]
PARK Y, PARK J, LEE. 2021 S, Arabidopsis thalianaSimultaneous profiling of and MO6-24/O transcriptomes by dual RNA-seq analysis [J]. Computational and structural biotechnology journal. 19: 2084-96.
- Salmon-Easy: An alignment-free RNA-seq quantitative strategy based on partial genome indexing
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May 2022
190 pages
ISBN:9781450396387
DOI:10.1145/3543377
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Published: 08 August 2022
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- the National Natural Science Foundation of China
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ICBBT 2022
ICBBT 2022: 2022 14th International Conference on Bioinformatics and Biomedical Technology
May 27 - 29, 2022
Xi'an, China
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