<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/44234?offset=170 https://bioinformaticsonline.com/bookmarks/view/39624/cogent-a-tool-for-reconstructing-the-coding-genome-using-high-quality-full-length-transcriptome-sequences Tue, 18 Jun 2019 05:33:04 -0500 https://bioinformaticsonline.com/bookmarks/view/39624/cogent-a-tool-for-reconstructing-the-coding-genome-using-high-quality-full-length-transcriptome-sequences <![CDATA[Cogent: a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences.]]> Cogent is a tool that identifies gene families and reconstructs the coding genome using high-quality transcriptome data without a reference genome, and can be used to check assemblies for the presence of these known coding sequences.
 

Cogent is a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences. It is designed to be used on Iso-Seq data and in cases where there is no reference genome or the ref genome is highly incomplete.

See a recent presentation on Cogent being applied to the Cuttlefish Iso-Seq data.

Cogent preliminary draft paper (updated 2016Dec version), Supplementary

Please see wiki for details on usage.

Address of the bookmark: https://github.com/Magdoll/Cogent

]]> Jit https://bioinformaticsonline.com/news/view/41230/curated-set-of-ribosomal-rna-rrna-reference-sequences-targeted-loci-with-verifiable-organism Sun, 23 Feb 2020 02:17:30 -0600 https://bioinformaticsonline.com/news/view/41230/curated-set-of-ribosomal-rna-rrna-reference-sequences-targeted-loci-with-verifiable-organism <![CDATA[Curated set of ribosomal RNA (rRNA) reference sequences (targeted loci) with verifiable organism]]> MCBI have a curated set of ribosomal RNA (rRNA) reference sequences (targeted loci) with verifiable organism sources and current names. This set is critical for correctly identifying and classifying prokaryotic (bacteria and archaea) and fungal samples. To provide easy access to these sequences, we recently added a separate rRNA/ITS databases section on the nucleotide BLAST page for these targeted sequences that makes it convenient to quickly identify source organisms. The new databases are:

               *16S ribosomal RNA (Bacteria and Archaea)

               *18S ribosomal RNA sequences (SSU) from Fungi type and reference material     

               *28S ribosomal RNA sequences (LSU) from Fungi type and reference material

               *Internal transcribed spacer region (ITS) from Fungi type and reference material

You can also download these from the BLAST db FTP area.  See the NCBI Insights post for more detail.

Useful links

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BLAST form with rRNA/ITS databases

BLAST db download

Targeted loci

If you have any questions or concerns, please contact blast-help@ncbi.nlm.nih.govhttps://jira.ncbi.nlm.nih.gov/images/icons/mail_small.gif

]]> Rahul Nayak https://bioinformaticsonline.com/news/view/42296/igblast-117-is-now-available-with-improved-identification-of-productive-v-gene-sequences Sun, 01 Nov 2020 16:52:58 -0600 https://bioinformaticsonline.com/news/view/42296/igblast-117-is-now-available-with-improved-identification-of-productive-v-gene-sequences <![CDATA[IgBLAST 1.17 is now available with improved identification of productive V gene sequences]]> A new release of IgBLAST (1.17), the popular package for classifying and analyzing immunoglobulin and T cell receptor sequences, is now available on the web and from the FTP site. The updated package is better at identifying productive V gene sequences. We added a new field , “V frame shift”, to the IgBLAST output to indicate whether the V gene translation frame contains a frame-shift. We have also updated the definition of a productive V(D)J sequence to now exclude those with internal frame shifts.

See the new IgBLAST manual on the NCBI GitHub site for more information on setting up and running IgBLAST.

If you have any questions or concerns, please email us at blast-help@ncbi.nlm.nih.gov

 

]]> Jit https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences Tue, 17 Sep 2024 02:34:57 -0500 https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences <![CDATA[SVbyEye: R Package to visualize alignments between two or multiple DNA sequences]]> R Package to visualize alignments between two or multiple DNA sequences including
a number of functionalities to facilitate processing of alignments in PAF format.

SVbyEye, an open-source R package to visualize and annotate sequence-to-sequence alignments along with various functionalities to process alignments in PAF format. The tool facilitates the characterization of complex SVs in the context of sequence homology helping resolve the mechanisms underlying their formation. Availability and implementation SVbyEye is available at https://github.com/daewoooo/SVbyEye.

Author: David Porubsky

Address of the bookmark: https://github.com/daewoooo/SVbyEye

]]> LEGE https://bioinformaticsonline.com/pages/view/44371/steps-to-find-all-the-repeats-in-the-genome Thu, 31 Aug 2023 02:43:28 -0500 https://bioinformaticsonline.com/pages/view/44371/steps-to-find-all-the-repeats-in-the-genome <![CDATA[Steps to find all the repeats in the genome !]]>

To find repeats in a genome from 2 to 9 length using a Perl script, you can use the RepeatMasker tool with the "--length" option[0]. Here's a step-by-step guide:

  1. Install RepeatMasker: First, you need to install RepeatMasker on your system. You can download it from the RepeatMasker website[0].
  1. Prepare the genome sequence: Make sure you have the genome sequence in a FASTA file format. Let's assume the file is named "genome.fasta".

./RepeatMasker -pa <number_of_processors> -nolow -norna -no_is -div <divergence_value> -lib RepeatMaskerLib.embl -gff -xsmall -small -poly -species <species_name> -dir <output_directory> -length <min_length>-<max_length> genome.fasta

Replace the following placeholders with appropriate values:

  • <number_of_processors>: The number of processors/threads you want to use for parallel processing.
  • <divergence_value>: The divergence value for the species you are analyzing. You can find divergence values for different species in the RepeatMasker documentation[0].
  • <species_name>: The name of the species you are analyzing.
  • <output_directory>: The directory where you want the output files to be saved.
  • <min_length> and <max_length>: The minimum and maximum lengths of the repeats you want to find (in this case, 2 and 9).
  1. Analyze the output: RepeatMasker will generate several output files, including a .out file. You can parse this file to extract the information you need. There is a Perl tool called "one_code_to_find_them_all.pl" that can help you parse RepeatMasker output files[0]. You can download it from the source provided.
  1. Use the provided Perl script: Once you have the "one_code_to_find_them_all.pl" script, you can run it to conveniently parse the RepeatMasker output files. Here's an example of how to use it:

perl one_code_to_find_them_all.pl --rm <RepeatMasker_out_file> --length <length_file>

 

Replace <RepeatMasker_out_file> with the path to your RepeatMasker .out file, and <length_file> with the path to a file containing the lengths of the reference elements.

This script will generate several output files, including .log.txt and .copynumber.csv, which contain quantitative information about the identified repeat elements.

Remember to adjust the parameters and options according to your specific needs and the characteristics of your genome.

]]> Neel