ArticleScientific reports2020
Raw transcriptomics data to gene specific SSRs: a validated free bioinformatics workflow for biologists.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- Assembly and comparative analysis of the complete mitochondrial genome of Polygonatum odoratum (Yuzhu), a medicine-food homologous plant.BMC plant biology · 2026Article
- Comparative transcriptomic and machine learning analysis identifies key genes and immune dysregulation in goats exposed to peste des petits ruminants virus.Virus genes · 2025Article
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- Assembly of the Complete Mitochondrial Genome ofInternational journal of molecular sciences · 2023Article
- Characterisation of the complete mitochondrial genome of Taraxacum mongolicum revealed five repeat-mediated recombinations.Plant cell reports · 2023Article
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- The complete plastomes of red fleshed pitaya (Physiology and molecular biology of plants : an international journal of functional plant biology · 2022Article
- Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent advances in next-generation sequencing technologies have paved the path for a considerable amount of sequencing data at a relatively low cost. This has revolutionized the genomics and transcriptomics studies. However, different challenges are now created in handling such data with available bioinformatics platforms both in assembly and downstream analysis performed in order to infer correct biological meaning. Though there are a handful of commercial software and tools for some of the procedures, cost of such tools has made them prohibitive for most research laboratories. While individual open-source or free software tools are available for most of the bioinformatics applications, those components usually operate standalone and are not combined for a user-friendly workflow. Therefore, beginners in bioinformatics might find analysis procedures starting from raw sequence data too complicated and time-consuming with the associated learning-curve. Here, we outline a procedure for de novo transcriptome assembly and Simple Sequence Repeats (SSR) primer design solely based on tools that are available online for free use. For validation of the developed workflow, we used Illumina HiSeq reads of different tissue samples of Santalum album (sandalwood), generated from a previous transcriptomics project. A portion of the designed primers were tested in the lab with relevant samples and all of them successfully amplified the targeted regions. The presented bioinformatics workflow can accurately assemble quality transcriptomes and develop gene specific SSRs. Beginner biologists and researchers in bioinformatics can easily utilize this workflow for research purposes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.