Fastq_clean: An optimized pipeline to clean the Illumina sequencing data with quality control

2014 ◽  
Author(s):  
Mi Zhang ◽  
Honghe Sun ◽  
Zhangjun Fei ◽  
Feng Zhan ◽  
Xiujun Gong ◽  
...  
Keyword(s):  
Quality Control ◽  
Illumina Sequencing ◽  
Sequencing Data ◽  
Illumina Sequencing Data

scholarly journals HTQC: a fast quality control toolkit for Illumina sequencing data

2013 ◽  
Vol 14 (1) ◽  
pp. 33 ◽  
Author(s):  
Xi Yang ◽  
Di Liu ◽  
Fei Liu ◽  
Jun Wu ◽  
Jing Zou ◽  
...  
Keyword(s):  
Quality Control ◽  
Illumina Sequencing ◽  
Sequencing Data ◽  
Illumina Sequencing Data

scholarly journals Complete Genome Sequence of the Autotrophic Acetogen Clostridium formicaceticum DSM 92T Using Nanopore and Illumina Sequencing Data

2017 ◽  
Vol 5 (21) ◽  
Author(s):  
Michael M. Karl ◽  
Anja Poehlein ◽  
Frank R. Bengelsdorf ◽  
Rolf Daniel ◽  
Peter Dürre
Keyword(s):  
Carbon Monoxide ◽  
Genome Sequence ◽  
Illumina Sequencing ◽  
Complete Genome Sequence ◽  
Complete Genome ◽  
Sequencing Data ◽  
Circular Chromosome ◽  
Content Type ◽  
Illumina Sequencing Data

ABSTRACT Here, we report the closed genome sequence of Clostridium formicaceticum, an Rnf- and cytochrome-containing autotrophic acetogen that is able to convert carbon monoxide to acetate using the Wood-Ljungdahl pathway. The genome consists of a circular chromosome (4.59 Mb).

scholarly journals QuicK-mer: A rapid paralog sensitive CNV detection pipeline

2015 ◽  
Author(s):  
Feichen Shen ◽  
Jeffrey Kidd
Keyword(s):  
High Throughput ◽  
Illumina Sequencing ◽  
Copy Number ◽  
Sequencing Data ◽  
Genome Copy ◽  
Genome Copy Number ◽  
Downstream Analysis ◽  
Cnv Detection ◽  
Illumina Sequencing Data ◽  
Control Regions

QuicK-mer is a unified pipeline for estimating genome copy-number from high-throughput Illumina sequencing data. QuicK-mer utilizes the Jellyfish application to efficiently tabulate counts of predefined sets of k-mers. The program performs GC-normalization using defined control regions and reports paralog-specific estimates of copy-number suitable for downstream analysis. The package is freely available at https://github.com/KiddLab/QuicK-mer

scholarly journals Identification of microRNAs in the green and red sectors of Amaranthus tricolor L. leaves based on Illumina sequencing data

2018 ◽  
Author(s):  
Shengcai Liu ◽  
Liyun Peng ◽  
Junfei Pan ◽  
Xiao Wang ◽  
Chunli Zhao ◽  
...  
Keyword(s):  
Illumina Sequencing ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Sequencing Data ◽  
Amaranthus Tricolor ◽  
Sequencing Platform ◽  
Transcriptome Database ◽  
Polymerase Chain ◽  
Illumina Sequencing Platform ◽  
Illumina Sequencing Data

Betalains are abundant in amaranth plants. Additionally, the betalain molecular structure and metabolic pathway differ from those of betanin in beet plants. To date, only a few studies have examined the regulatory roles of miRNAs in betalain biosynthesis in plants. Thus, we constructed small RNA libraries for the red and green sectors of amaranth leaves to identify miRNAs associated with betalain biosynthesis. We identified 198 known and 41 novel miRNAs. Moreover, 216 miRNAs were distributed in 44 miRNA families, including miR156, miR159, miR160, miR166, miR172, miR319, miR167, miR396, and miR398. An analysis of all unigene sequences in an amaranth transcriptome database resulted in the detection of 493 target genes for the 239 screened miRNAs. The targets included SPL2, ARF18, ARF6, and NAC. A quantitative real-time polymerase chain reaction validation of 20 miRNAs and nine target genes revealed expression-level differences between the red and green sectors of amaranth leaves. This study involved the application of an Illumina sequencing platform to identify miRNAs regulating betalain metabolism in amaranth plants. The data presented herein may provide insights into the molecular mechanisms underlying the regulation of betalain biosynthesis in amaranth and other plant species.

scholarly journals AlmostSignificant: Simplifying quality control of high-throughput sequencing data

2016 ◽  
Author(s):  
Joseph Ward ◽  
Christian Cole ◽  
Melanie Febrer ◽  
Geoffrey Barton
Keyword(s):  
Quality Control ◽  
Dna Sequencing ◽  
Illumina Sequencing ◽  
High Throughput Sequencing ◽  
Sequencing Data ◽  
Multiple Sources ◽  
Meta Data ◽  
Sequencing Technologies ◽  
High Throughput Sequencing Data

AbstractMotivationThe current generation of DNA sequencing technologies produce a large amount of data quickly. All of these data need to pass some form of quality control processing and checking before they can be used for any analysis. The large number of samples that are run through Illumina sequencing machines makes the process of quality control an onerous and time-consuming task that requires multiple pieces of information from several sources.ResultsAlmostSignificant is an open-source platform for aggregating multiple sources of quality metrics as well as meta-data associated with DNA sequencing runs from Illumina sequencing machines. AlmostSignificant is a graphical platform to streamline the quality control of DNA sequencing data, to collect and store these data for future reference and to collect extra meta-data associated with the sequencing runs to check for errors and monitor the volume of data produced by the associated machines. AlmostSignificant has been used to track the quality of over 80 sequencing runs covering over 2500 samples produced over the last three years.AvailabilityThe code and documentation for AlmostSignificant is freely available at https://github.com/bartongroup/[email protected], [email protected]

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