Identifying transposon insertion sites from multiplexed NGS data

Transposon mutagenesis is a common approach for investigating gene function in bacterial genomes by selecting for clones where the transposon inserting into the genome has generated a specific phenotype. You can then simply sequence the entire genome of each clone by NGS to identify the transposon insertion site. To lower the cost of such experiments, […]

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Human Transcriptome RNA-Seq Analysis Using MacVector

With MacVector Pro and Assembler you can use Bowtie to perform RNA-Seq analyses using NGS data. The interface even has specialized output tabs listing the coverage information and statistics for each annotated CDS and gene feature on the genome. There is an example tutorial in the /Applications/MacVector/Documentation folder called “RNASeq Expression Analysis Tutorial.pdf” that illustrate […]

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Use a right-click in the Editor tab to see if your contig can be circularized

MacVector incorporates no less than THREE different de novo assemblers, phrap, velvet and SPAdes. While all are great assemblers, with each having their own specific advantages, none of them will generate a circular sequence from input reads. However, MacVector also includes a tool to help you with this. If you are assembling reads representing plasmid […]

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Import Multi-Sequence Genbank Files into an Assembly Project for easy access to Features

There are many genomes in the Genbank database that cannot be downloaded as single annotated sequences. These might be large multi-chromosome eukaryotic genomes, but, increasingly, partially sequenced bacterial chromosomes where the major contigs have been annotated using the NCBI annotation pipeline. Typically, when you encounter these, there are options to download annotated versions of these […]

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Optimizing Align To Folder Parameters for use with NGS Data

You can use the Database | Align To Folder function to scan large fasta or fastq files containing NGS data to find and retrieve just those reads that match a specific target sequence. The search is aware of paired-end reads, so when you retrieve hits, both reads of a pair will be saved into a […]

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What can MacVector do for my lab?

Here’s what MacVector can do for your lab. Comparing sequences Whatever type of alignment your sequence needs, there’s a tool in MacVector. CRISPR Indel Analysis: Identify insertions and deletions following CRISPR editing of a target. Compare Genomes: Compares two related annotated genomes to identify identical, similar and weakly similar features. Sequence assembly of NGS data […]

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Comparing multiple reference assemblies with MacVector 17

MacVector 17 has a greatly improved Assembly Projects manager, for better organization of multiple sequencing datasets, multiple references sequences and repeated jobs. Every time you run a new assembly job (either a reference assembly or de novo). A new job object is created in the Assembly Project window contains resulting contigs and any unaligned reads […]

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Balancing Velvet KMER and coverage

The Velvet assembly algorithm in MacVector is blazingly fast and generates excellent assemblies. However, you do have to be careful when assembling NGS data to be sure that the parameters you submit are appropriate for the data you are assembling in order to get optimal results. By far the most important parameter is the KMER […]

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Use a right-click in the Editor tab to see if your contig can be circularized

MacVector 16 incorporates no less than THREE different de novo assemblers, phrap, velvet and SPAdes. While all are great assemblers, with each having their own specific advantages, none of them will generate a circular sequence from input reads. However, MacVector 16 also includes a new feature to help you with this. If you are assembling […]

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Assemble bacterial genomes in minutes on your Mac laptop

MacVector with Assembler contains some remarkably powerful algorithms for assembling Next Generation Sequencing (NGS) data. Not so long ago, you needed a powerful Linux server with lots of memory for de novo assembly of whole genomes. But with advances in the efficiency of algorithms and improvements in hardware, it is now possible to assemble quite […]

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