Our normalisation procedure is based on the addition of a proportional number of S. Typhimurium cells to each sample of E. coli cells immediately before harvesting RNA. All reads were first mapped to the E. coli MG1655 genome using CLC Genomics Workbench (Version 8.0; default parameters except that a perfect match was required). Unmapped reads were mapped to the S. Typhimurium 14028s genome (same parameters as above). The number of mapped S. Typhimurium reads, for each E. coli sample, was used to determine a correction factor for each sample. For example, if Sample A has twice as many S. Typhimurium reads as Sample B, the correction factor for Sample A will be twice that for Sample B. Having calculated a correction factor for each sample, we remapped all sequence reads to the S. Typhimurium 14028s genome using CLC Genomics Workbench (same parameters as above). Unmapped reads were then mapped to the E. coli MG1655 genome using CLC Genomics Workbench (same parameters as above). Total read coverage per gene was calculated using a custom Python script. These values were normalised to the length of the gene, and further normalised using the correction factor (described above). Raw data are available from the ArrayExpress database using accession number E-MTAB-4751.
Clc genomics workbench
Manufactured by Qiagen
Sourced in Denmark, Germany, United States, Japan, New Zealand, Netherlands
The CLC Genomics Workbench is a comprehensive software platform for analyzing and visualizing biological sequence data. It provides a range of tools and functionalities for tasks such as sequence alignment, genome assembly, variant calling, and data exploration.
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Lab products found in correlation
Trizol reagent, by Thermo Fisher Scientific (27 mentions)
Nextseq 500, by Illumina (24 mentions)
Miseq platform, by Illumina (21 mentions)
Hiseq 2500, by Illumina (18 mentions)
Hiseq 2000, by Illumina (17 mentions)
Trizol, by Thermo Fisher Scientific (13 mentions)
Nextera xt dna library preparation kit, by Illumina (12 mentions)
Rneasy mini kit, by Qiagen (11 mentions)
Dneasy blood and tissue kit, by Qiagen (11 mentions)
Nebnext rrna depletion kit, by New England Biolabs (11 mentions)
Miseq system, by Illumina (10 mentions)
Nebnext ultra directional rna library prep kit, by New England Biolabs (10 mentions)
Bioanalyzer, by Agilent Technologies (9 mentions)
2100 bioanalyzer, by Agilent Technologies (8 mentions)
Qiaamp viral rna mini kit, by Qiagen (8 mentions)
Agilent 2100 bioanalyzer, by Agilent Technologies (7 mentions)
Miseq sequencer, by Illumina (7 mentions)
Qiaseq fx dna library kit, by Qiagen (7 mentions)
Fastqc, by Babraham Bioinformatics (6 mentions)
Miseq reagent kit v3, by Illumina (6 mentions)
774 protocols using clc genomics workbench
1
Normalizing RNA-seq Data with Spiked-in Salmonella
2
Phylogenetic Analysis of Viral Genomes
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Genomic comparison of the newly sequenced complete viral genomes was visualized using Geneious (version 2022.1.1). The sequence similarity between the selected viral sequences was identified against representative viral sequences by MAFFT alignment L-INS-I in Geneious (version 2022.1.1, Biomatters, Ltd., Auckland, New Zealand).
For phylogenetic analyses, representative viral genome or gene sequences were downloaded from GenBank, and virus-specific trees were constructed using CLC Genomics Workbench (version 9.0.1) and Geneious software (version 2022.1.1, Biomatters, New Zealand). Amino acid sequences of protein-coding genes and nucleotide sequences of the selected partial genes were aligned using the MAFTT L-INS-I algorithm implemented in Geneious (version 7.388) (49 (link)). To determine the best-fit model to construct phylogenetic analyses, a model test was performed using CLC Genomics Workbench (version 9.5.4) using default parameters, favoring a general-time-reversible model gamma distribution rate variation and a proportion of invariable sites (GTR + G + I). Phylogenetic analyses for nucleotide and protein sequences were performed using the GTR and WAG substitution model, respectively, with 1,000 bootstrap support in CLC Genomics Workbench (version 9.0.1).
For phylogenetic analyses, representative viral genome or gene sequences were downloaded from GenBank, and virus-specific trees were constructed using CLC Genomics Workbench (version 9.0.1) and Geneious software (version 2022.1.1, Biomatters, New Zealand). Amino acid sequences of protein-coding genes and nucleotide sequences of the selected partial genes were aligned using the MAFTT L-INS-I algorithm implemented in Geneious (version 7.388) (49 (link)). To determine the best-fit model to construct phylogenetic analyses, a model test was performed using CLC Genomics Workbench (version 9.5.4) using default parameters, favoring a general-time-reversible model gamma distribution rate variation and a proportion of invariable sites (GTR + G + I). Phylogenetic analyses for nucleotide and protein sequences were performed using the GTR and WAG substitution model, respectively, with 1,000 bootstrap support in CLC Genomics Workbench (version 9.0.1).
3
Phylogenetic Analysis of Viral Genomes
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Genomic features of the newly sequenced viral genomes were visualised using Geneious (version 10.2.2). Sequence similarity percentages between representative viruses were determined using tools available in Geneious (version 10.2.2).
For phylogenetic analyses, representative viral genome or gene sequences were downloaded from GenBank, and virus-specific trees were constructed using CLC Genomics Workbench (version 9.5.4) and Geneious software (version 10.2.2, Biomatters, New Zealand). Amino acid sequences of protein-coding genes and nucleotide sequences of the selected partial genes were aligned using the MAFTT L-INS-I algorithm implemented in Geneious (version 7.388)65 (link). To determine the best-fit model to construct phylogenetic analyses, a model test was performed using CLC Genomics Workbench (version 9.5.4) using default parameters, favouring a general-time-reversible model with gamma distribution rate variation and a proportion of invariable sites (GTR + G + I). Phylogenetic analyses for nucleotide and protein sequences were performed using the GTR and WAG substitution model, respectively, with 1000 bootstrap support in CLC Genomics Workbench (version 9.5.4).
For phylogenetic analyses, representative viral genome or gene sequences were downloaded from GenBank, and virus-specific trees were constructed using CLC Genomics Workbench (version 9.5.4) and Geneious software (version 10.2.2, Biomatters, New Zealand). Amino acid sequences of protein-coding genes and nucleotide sequences of the selected partial genes were aligned using the MAFTT L-INS-I algorithm implemented in Geneious (version 7.388)65 (link). To determine the best-fit model to construct phylogenetic analyses, a model test was performed using CLC Genomics Workbench (version 9.5.4) using default parameters, favouring a general-time-reversible model with gamma distribution rate variation and a proportion of invariable sites (GTR + G + I). Phylogenetic analyses for nucleotide and protein sequences were performed using the GTR and WAG substitution model, respectively, with 1000 bootstrap support in CLC Genomics Workbench (version 9.5.4).
4
Genomic Analysis of Novel Psittaciform Chaphamaparvovirus
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The genomic features of the novel psittaciform chaphamaparvovirus 2 (PsChPV-2) genome were visualised using Geneious (version 10.2.2). Sequence similarity percentages between representative viruses were determined using tools available in Geneious (version 10.2.2). For phylogenetic analyses, demonstrative parvoviral gene sequences were downloaded from GenBank and trees were constructed using CLC Genomics Workbench (version 9.5.4). The amino acid sequences of protein-coding genes of the selected genes were aligned using the MAFTT L-INS-I algorithm implemented in Geneious (version 7.388) [27 (link)]. Phylogenetic analyses for protein sequences were performed using the WAG substitution model, with 1000 bootstrap replicates in CLC Genomics Workbench (version 9.5.4).
5
Strand-Specific RNA-Seq Analysis Workflow
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Paired-end demultiplexed fastq files were generated using bcl2fastq2 (Illumina, v2.17), from NovaSeq6000 SP4 reagent’s bcl files. Initial quality control was performed using FastQC v0.11.8 and multiqc v1.7. Fastq files were imported batch wise, trimmed for adapter sequences followed by quality trimming using CLC Genomics Workbench (CLC Bio, v23.0.3). The imported high-quality reads were mapped against gene regions and transcripts annotated by ENSEMBL v99 hg38 using the RNA-Seq Analysis tool v2.7 (CLC Genomics Workbench), only matches to the reverse strand of the genes were accepted (using the strand-specific reverse option). Differential gene expression analysis between the sample groups was done using the Differential Expression for RNA-seq tool v2.8, where the normalization method was set as TMM. Differential expression between the groups was tested using a control group, outliers were downweighed, and filter on average expression for FDR correction was enabled.
6
Chloroplast Genome Assembly and Annotation
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Chloroplast genome assembly was conducted by the de novo assembly protocol [23 (link)] via the Phyzen bioinformatics pipeline (http://phyzen.com ). The DNA of A. divaricata was sequenced to produce 8,361,496 raw reads with a length of 301 bp. Low-quality sequences (Phred score < 20) were trimmed using CLC Genomics Workbench (version 6.04; CLC Inc., Arhus, Denmark). After trimming, the library for A. racemosa included 6,991,585 reads. Then, de novo assembly was implemented using the CLC Genome Assembler (http://www.clcbio.com/products/clc-assembly-cell ). A total of 107,248 reads were aligned and selected form chloroplast contigs using the nucmer tool in MUMmer [24 (link)]. The draft genome contigs were merged into a single contig by joining overlapping terminal sequences of each contig. Additionally, the chloroplast genome coverage was estimated using CLC Genomics Workbench (version 6.04; CLC Inc.).
The protein-coding genes, transfer RNAs (tRNAs), and ribosomal RNAs (rRNAs) in the chloroplast genome were predicted and annotated using Dual Organellar GenoMe Annotator (DOGMA) with the default parameters [25 (link)] and manually edited by comparison with the published chloroplast genome sequences of Campanulaceae. tRNAs were confirmed using tRNAscan-SE [26 (link)]. A circular chloroplast genome map was drawn using the OGDRAW program [27 (link)].
The protein-coding genes, transfer RNAs (tRNAs), and ribosomal RNAs (rRNAs) in the chloroplast genome were predicted and annotated using Dual Organellar GenoMe Annotator (DOGMA) with the default parameters [25 (link)] and manually edited by comparison with the published chloroplast genome sequences of Campanulaceae. tRNAs were confirmed using tRNAscan-SE [26 (link)]. A circular chloroplast genome map was drawn using the OGDRAW program [27 (link)].
7
Phylogenetic Analysis of G. lateralis GPCRs
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To further annotate the G. lateralis GPCRs for phylogenetic analysis, the seven TM domains of all GPCRs were extracted and compiled with the reference list. Multiple sequence alignment was carried out using MUSCLE tools implemented in CLC Genomics Workbench (CLC Bio, version 10.0). The sequence alignment file was used to generate a phylogenetic tree with CLC Genomics Workbench (Neighbor-joining phylogeny with 1,000 bootstraps). The lists of GPCRs used for phylogeny are given in Additional file 1 .
8
Paired-end RNA-Seq Differential Expression
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Paired-end demultiplexed fastq files were generated using bcl2fastq2 (Illumina, v2.17), from NovaSeq6000 SP4 reagent's bcl files. Initial quality control was performed using FastQC v0.11.8 and multiqc v1.7. Fastq files were imported batch wise, trimmed for adapter sequences followed by quality trimming using CLC Genomics Workbench (CLC Bio, v23.0.3). The imported high-quality reads were mapped against gene regions and transcripts annotated by ENSEMBL v99 hg38 using the RNA-Seq Analysis tool v2.7 (CLC Genomics Workbench), only matches to the reverse strand of the genes were accepted (using the strand-specific reverse option). Differential gene expression analysis between the sample groups was done using the Differential Expression for RNA-seq tool v2.8, where the normalization method was set as TMM. Differential expression between the groups was tested using a control group, outliers were downweighed, and filter on average expression for FDR correction was enabled.
9
RNA-Seq Data Analysis of Staphylococcus aureus
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RNA-seq data were analyzed using CLC Genomics Workbench (version 7.5.2), and reads were mapped to the S. aureus MW2 genome (GenBank accession number NC_003923 ). Data were log2 transformed and normalized using quantile normalization on transformed expression values and the quality of replicates assessed by principal-component analysis. After confirming that all replicates clustered together, differential gene expression analysis was performed comparing each of the phosphomimetic RR-expressing samples with the pRMC2-containing control samples. Differential gene expression analysis was performed using the built-in algorithm of CLC Genomics Workbench (version 7.5.2) and the following settings: total count filter cutoff, 5.0; estimate tagwise dispersion, yes; comparison, against reference; reference name, pRMC2; false discovery rate (FDR) corrected, yes. Genes were considered to be significantly regulated when a fold change of more than twofold was observed and the P value after FDR correction was below 0.05.
10
Phylogenetic Analysis of Plant DNA Methylation
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The polypeptide sequences of DNA methylases and demethylases of selected plant species (Supplementary Table S3 ) from the Rosids clade (NCBI: taxid: 71275), including the sequences of the newly identified DNA methylases and demethylase of the hop plant, were used for phylogenetic analysis. Multiple sequence alignment was performed using the algorithm MUSCLE with default parameters implemented in CLC Genomics Workbench (22.0). The three groups of DNA methylases and one group of DNA demethylases were aligned together with their homologs in four separate alignments. Alignments were manually curated by truncating all positions with gaps and missing data, followed by a construction of phylogenetic trees using the maximum likelihood method based on the WAG protein substitution model using default parameters implemented in CLC Genomics Workbench (22.0). The reliability of the tree nodes was tested with 1000 bootstrap replicates.
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