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Illumina Inc genome analyzer ii
Genome Analyzer Ii, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 92/100, based on 345 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/genome analyzer ii/product/Illumina Inc
Average 92 stars, based on 345 article reviews
Price from $9.99 to $1999.99
genome analyzer ii - by Bioz Stars, 2020-09
92/100 stars

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Sequencing:

Article Title: A Poisson hierarchical modelling approach to detecting copy number variation in sequence coverage data
Article Snippet: .. All seven genomes underwent whole genome sequencing on the Illumina Genome Analyzer II (54/76-base paired read) platform and processed as described elsewhere [ ]. .. In brief, multiple alignment (bam) files were generated from fastq files of each whole genome sequencing data set after mapping the reads onto the 3D7 reference genome (version 3.0) using the smalt software ( http://www.sanger.ac.uk/resources/software/smalt/ ).

Article Title: Asymmetric purine-pyrimidine distribution in cellular small RNA population of papaya
Article Snippet: .. Thus constructed library was sequenced with the Sequencing-by-synthesis (SBS) technology on an Illumina Genome Analyzer II. .. The final sequence was processed to remove 3’ and 5’ adapters and used for downstream analysis.

Flow Cytometry:

Article Title: MicroRNAs and their putative targets in Brassica napus seed maturation
Article Snippet: .. The libraries were quantified and loaded on individual lanes of a flow-cell and sequenced on a Genome Analyzer II for 36 cycles following the manufacturer's protocols (Illumina). ..

Generated:

Article Title: Lineage-specific roles of the cytoplasmic polyadenylation factor CPEB4 in the regulation of melanoma drivers
Article Snippet: .. Twenty nanograms of RNA per sample were processed with Ribo-Zero Gold Kit (Epicentre, Cat. No. RZHM11106/RZG1224) for ribosomal RNAs removal. cDNA libraries were generated and sequenced on Illumina Genome Analyzer II × with SBS TruSeq v5 reagents following manufacturer's protocols. ..

Construct:

Article Title: Asymmetric purine-pyrimidine distribution in cellular small RNA population of papaya
Article Snippet: .. Thus constructed library was sequenced with the Sequencing-by-synthesis (SBS) technology on an Illumina Genome Analyzer II. .. The final sequence was processed to remove 3’ and 5’ adapters and used for downstream analysis.

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  • 88
    Illumina Inc illumina ga ii instrument
    Distribution of percentages of a minor variant for SNPs as recovered by <t>Illumina</t> sequencing. Red: homozygous SNPs, blue: heterozygous SNPs. Solid line: HapMap SNPs, dashed line: new SNPs.
    Illumina Ga Ii Instrument, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 88/100, based on 12 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/illumina ga ii instrument/product/Illumina Inc
    Average 88 stars, based on 12 article reviews
    Price from $9.99 to $1999.99
    illumina ga ii instrument - by Bioz Stars, 2020-09
    88/100 stars
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    86
    Illumina Inc sequencing illumina genome analyzer platform
    Percentage of total and unique clean tags that are mapped to the reference Verticillium dahliae genome VDLs 17 in the non-germinated (A) and germinated (B) microsclerotium libraries in relation to the total number of tags. New unique tag (y axis) of VDMG-b and VDM libraries decreased as the <t>Illumina</t> sequencing increased (x axis).
    Sequencing Illumina Genome Analyzer Platform, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/sequencing illumina genome analyzer platform/product/Illumina Inc
    Average 86 stars, based on 1 article reviews
    Price from $9.99 to $1999.99
    sequencing illumina genome analyzer platform - by Bioz Stars, 2020-09
    86/100 stars
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    86
    Illumina Inc ga ii rna seq
    The percentages of probe sets in mapping groups A, B, C, and D. The percentages of <t>Affymetrix</t> probe sets in four mapping groups A, B, C, and D for the six <t>RNA-Seq</t> gene sets are shown in stacked bar charts. The data set comprises 62 Affymetrix Rat_230_2 arrays and 62 RNA-Seq assays from the same set of 62 rat liver RNA samples. The microarray data were normalized with MAS5, and the same RNA-Seq raw data were analyzed by six independent data analysis teams with a variety of analysis pipelines, that is, P1 (NCBI Magic), P2 (Novoalign with RefSeq gene models), P3 (Bwa + RefSeq RNAs), P4 (Tophat + HTSeq with RefSeq gene models), P5 (Bowtie + RSEM with Ensembl gene models), and P6 (Tophat + cufflinks de novo assembly). The Affymetrix probe sets (31,099 in total) were separately mapped to the six RNA-Seq gene sets. The mappings to P1, P2, P3, and P4 gene sets are based on the gene ID mapping approach, while mappings to P5 and P6 gene sets are based on the genome location mapping.
    Ga Ii Rna Seq, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 86/100, based on 6 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/ga ii rna seq/product/Illumina Inc
    Average 86 stars, based on 6 article reviews
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    ga ii rna seq - by Bioz Stars, 2020-09
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    Image Search Results


    Distribution of percentages of a minor variant for SNPs as recovered by Illumina sequencing. Red: homozygous SNPs, blue: heterozygous SNPs. Solid line: HapMap SNPs, dashed line: new SNPs.

    Journal: PLoS ONE

    Article Title: Detection of Genomic Variation by Selection of a 9 Mb DNA Region and High Throughput Sequencing

    doi: 10.1371/journal.pone.0006659

    Figure Lengend Snippet: Distribution of percentages of a minor variant for SNPs as recovered by Illumina sequencing. Red: homozygous SNPs, blue: heterozygous SNPs. Solid line: HapMap SNPs, dashed line: new SNPs.

    Article Snippet: High throughput single-end sequencing was performed using the Illumina GA-II instrument.

    Techniques: Variant Assay, Sequencing

    Schematic representation of imGLAD’s pipeline. imGLAD has two main components. (A) The first part (training) consists of a learning procedure, in which a set of in-silico generated datasets are fitted through a logistic model that aims to separate positive from negative datasets. For this, a database of 200 genomes is used to generate the simulated Illumina reads of these datasets. Reads simulated from the target genome are then incorporated into half of the simulated datasets. The resulting datasets are marked as positive for training while the other half is marked as negative. Sequencing depth and breadth of the target (reference) genome are calculated for each dataset. A logistic function is then fitted to the data to separate positive from negative examples. The regression parameters are stored for further use. (B) The second part (estimation) consists of estimating the sequencing breadth and/or depth values of the target genome provided by the (recruited) reads of the experimental metagenomes, and comparison of the derived sequencing depth and breadth values to those of the logistic function from the training step.

    Journal: PeerJ

    Article Title: imGLAD: accurate detection and quantification of target organisms in metagenomes

    doi: 10.7717/peerj.5882

    Figure Lengend Snippet: Schematic representation of imGLAD’s pipeline. imGLAD has two main components. (A) The first part (training) consists of a learning procedure, in which a set of in-silico generated datasets are fitted through a logistic model that aims to separate positive from negative datasets. For this, a database of 200 genomes is used to generate the simulated Illumina reads of these datasets. Reads simulated from the target genome are then incorporated into half of the simulated datasets. The resulting datasets are marked as positive for training while the other half is marked as negative. Sequencing depth and breadth of the target (reference) genome are calculated for each dataset. A logistic function is then fitted to the data to separate positive from negative examples. The regression parameters are stored for further use. (B) The second part (estimation) consists of estimating the sequencing breadth and/or depth values of the target genome provided by the (recruited) reads of the experimental metagenomes, and comparison of the derived sequencing depth and breadth values to those of the logistic function from the training step.

    Article Snippet: The B. anthracis datasets were made previously available by Be and colleagues, and consisted of a soil microbial community DNA sample spiked with known quantities (genome equivalents) of DNA of B. anthracis strain Ames , and sequenced using the Illumina GA-II technology ( ).

    Techniques: In Silico, Generated, Sequencing, Derivative Assay

    Percentage of total and unique clean tags that are mapped to the reference Verticillium dahliae genome VDLs 17 in the non-germinated (A) and germinated (B) microsclerotium libraries in relation to the total number of tags. New unique tag (y axis) of VDMG-b and VDM libraries decreased as the Illumina sequencing increased (x axis).

    Journal: PLoS ONE

    Article Title: Whole Genome Wide Expression Profiles on Germination of Verticillium dahliae Microsclerotia

    doi: 10.1371/journal.pone.0100046

    Figure Lengend Snippet: Percentage of total and unique clean tags that are mapped to the reference Verticillium dahliae genome VDLs 17 in the non-germinated (A) and germinated (B) microsclerotium libraries in relation to the total number of tags. New unique tag (y axis) of VDMG-b and VDM libraries decreased as the Illumina sequencing increased (x axis).

    Article Snippet: Illumina sequencing Illumina Genome Analyzer platform (GA II) was used to perform a Serial Analysis of Gene Expression (SAGE)-derived Digital Gene Expression (DGE) analysis for the transcriptome of germinated and non-germinated V. dahliae microsclerotia (BGI, China).

    Techniques: Sequencing

    The percentages of probe sets in mapping groups A, B, C, and D. The percentages of Affymetrix probe sets in four mapping groups A, B, C, and D for the six RNA-Seq gene sets are shown in stacked bar charts. The data set comprises 62 Affymetrix Rat_230_2 arrays and 62 RNA-Seq assays from the same set of 62 rat liver RNA samples. The microarray data were normalized with MAS5, and the same RNA-Seq raw data were analyzed by six independent data analysis teams with a variety of analysis pipelines, that is, P1 (NCBI Magic), P2 (Novoalign with RefSeq gene models), P3 (Bwa + RefSeq RNAs), P4 (Tophat + HTSeq with RefSeq gene models), P5 (Bowtie + RSEM with Ensembl gene models), and P6 (Tophat + cufflinks de novo assembly). The Affymetrix probe sets (31,099 in total) were separately mapped to the six RNA-Seq gene sets. The mappings to P1, P2, P3, and P4 gene sets are based on the gene ID mapping approach, while mappings to P5 and P6 gene sets are based on the genome location mapping.

    Journal: Genome Biology

    Article Title: An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era

    doi: 10.1186/s13059-014-0523-y

    Figure Lengend Snippet: The percentages of probe sets in mapping groups A, B, C, and D. The percentages of Affymetrix probe sets in four mapping groups A, B, C, and D for the six RNA-Seq gene sets are shown in stacked bar charts. The data set comprises 62 Affymetrix Rat_230_2 arrays and 62 RNA-Seq assays from the same set of 62 rat liver RNA samples. The microarray data were normalized with MAS5, and the same RNA-Seq raw data were analyzed by six independent data analysis teams with a variety of analysis pipelines, that is, P1 (NCBI Magic), P2 (Novoalign with RefSeq gene models), P3 (Bwa + RefSeq RNAs), P4 (Tophat + HTSeq with RefSeq gene models), P5 (Bowtie + RSEM with Ensembl gene models), and P6 (Tophat + cufflinks de novo assembly). The Affymetrix probe sets (31,099 in total) were separately mapped to the six RNA-Seq gene sets. The mappings to P1, P2, P3, and P4 gene sets are based on the gene ID mapping approach, while mappings to P5 and P6 gene sets are based on the genome location mapping.

    Article Snippet: We first mapped Affymetrix Rat_230_2 arrays to Illumina GA II RNA-Seq using the method depicted in Figure a (see also ).

    Techniques: RNA Sequencing Assay, Microarray

    The strategy for cross-platform gene mapping and the consistency of cross-platform gene expression measurements. The microarray probes/probe sets are mapped to RNA-Seq genes in one of two ways: public gene ID mapping or genome location mapping (a) . Using the gene ID mapping approach requires that one of the following public gene IDs be available: gene symbol, RefSeq transcript ID, Ensembl gene ID, or Entrez gene ID. Using the genome location mapping requires an RNA-Seq gene annotation file in either the Gene Transfer Format (GTF) or the General Feature Format (GFF). The process produces separate mapping lists for microarrays and RNA-Seq. Each of them consists of A, B, C, and D groups. Group A for microarrays corresponds to the group A in RNA-Seq. The microarray group B is a subset of RNA-Seq group C, and vice versa . The D group for microarrays and for RNA-Seq contain genes and probes/probe sets that cannot be mapped between the two platforms. The intensities of Affymetrix microarray probe sets in mapping groups A, B, and C are separately compared to those of RNA-Seq gene counts in panels (b) , (c) , and (d) for one of the eight RNA samples in the NCTR toxicogenomics data set. The microarray data are from Rat_230_2 arrays normalized with the MAS5 algorithm, and the RNA-Seq reads are from the Illumina GA II platform with the single-end 36 base pairs RNA-Seq protocol and gene counts from the P2 pipeline (Novoalign with RefSeq rat gene models). The mappings from microarray probe sets to RNA-Seq genes are based on the genome location mapping approach.

    Journal: Genome Biology

    Article Title: An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era

    doi: 10.1186/s13059-014-0523-y

    Figure Lengend Snippet: The strategy for cross-platform gene mapping and the consistency of cross-platform gene expression measurements. The microarray probes/probe sets are mapped to RNA-Seq genes in one of two ways: public gene ID mapping or genome location mapping (a) . Using the gene ID mapping approach requires that one of the following public gene IDs be available: gene symbol, RefSeq transcript ID, Ensembl gene ID, or Entrez gene ID. Using the genome location mapping requires an RNA-Seq gene annotation file in either the Gene Transfer Format (GTF) or the General Feature Format (GFF). The process produces separate mapping lists for microarrays and RNA-Seq. Each of them consists of A, B, C, and D groups. Group A for microarrays corresponds to the group A in RNA-Seq. The microarray group B is a subset of RNA-Seq group C, and vice versa . The D group for microarrays and for RNA-Seq contain genes and probes/probe sets that cannot be mapped between the two platforms. The intensities of Affymetrix microarray probe sets in mapping groups A, B, and C are separately compared to those of RNA-Seq gene counts in panels (b) , (c) , and (d) for one of the eight RNA samples in the NCTR toxicogenomics data set. The microarray data are from Rat_230_2 arrays normalized with the MAS5 algorithm, and the RNA-Seq reads are from the Illumina GA II platform with the single-end 36 base pairs RNA-Seq protocol and gene counts from the P2 pipeline (Novoalign with RefSeq rat gene models). The mappings from microarray probe sets to RNA-Seq genes are based on the genome location mapping approach.

    Article Snippet: We first mapped Affymetrix Rat_230_2 arrays to Illumina GA II RNA-Seq using the method depicted in Figure a (see also ).

    Techniques: Expressing, Microarray, RNA Sequencing Assay