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  • BioStar posted to the wire 2272 days ago
  • BioStar posted to the wire 2272 days ago
    Computational Biology and Bioinformatics in Nigeria https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3998874/ #Nigeria #Bioinformatics #Scope
  • Rahul Nayak posted to the wire 2272 days ago
    Multi-line fasta to single line fasta $ perl -pe '/^>/ ? print "\n" : chomp' in.fasta | tail -n +2 > out.fasta #Multiline #Singleline #Fasta
  • Rahul Nayak published a blog post Setting python version as default on Linux 2273 days ago
    If you have a later version than 2.6 you'll need to set 2.6 as the default Python.
  • Rahul Nayak posted to the wire 2273 days ago
    Snakemake install Ubuntu $ sudo apt-get install snakemake #snakemake #Ubuntu #Install
  • Snakemake is a workflow engine that provides a readable Python-based workflow definition language and a powerful execution environment that scales from single-core workstations to compute clusters without modifying the workflow. 
  • You can also bioinformatics tools at https://www.journals.elsevier.com/information-and-software-technology/short-communications/information-and-software-technology-now-publishing-short-com
  • Anjana is now a friend with BioStar 2277 days ago
  • BioStar is now a friend with Anjana 2277 days ago
  • Jit created a new bio-script Update zsh on Ubuntu ! 2278 days ago
  • Jit created a new bio-script Downloading GATK ! 2278 days ago
  • Neel uploaded the file Applied Statistics for Bioinformatics using R in the group R and Bioconductor 2278 days ago
    The purpose of this book is to give an introduction into statistics in order to solve some problems of bioinformatics. Statistics provides procedures to explore and visualize data as well as to test biological hypotheses. The book intends to be...
  • Neel commented on a page titled List of Bioinformatics and Computational Biology Journals 2279 days ago
    Publish scripts at The Journal of Open Source Software http://joss.theoj.org/about
  • STELLAR is very practical and fast on very long sequences which makes it a suitable new tool for finding local alignments between genomic sequences under the edit distance model. Binaries are freely available for Linux, Windows, and Mac OS X...
  • Installing goleft ➜ falconUnzip_assembly bioconda install goleftzsh: command not found: bioconda➜ falconUnzip_assembly conda install goleft Solving environment: done ## Package Plan ## environment location: /home/urbe/anaconda3 added / updated...
  • indexcov, an efficient estimator of whole-genome sequencing coverage to rapidly identify samples with aberrant coverage profiles, reveal large-scale chromosomal anomalies, recognize potential batch effects, and infer the sex of a...
    Comments
    • Jit 2279 days ago

      Installing goleft

      ➜ falconUnzip_assembly bioconda install goleft
      zsh: command not found: bioconda
      ➜ falconUnzip_assembly conda install goleft
      Solving environment: done

      ## Package Plan ##

      environment location: /home/urbe/anaconda3

      added / updated specs:
      - goleft


      The following packages will be downloaded:

      package | build
      ---------------------------|-----------------
      ca-certificates-2018.8.24 | ha4d7672_0 136 KB conda-forge
      certifi-2018.8.24 | py36_1 139 KB conda-forge
      goleft-0.1.18 | 1 6.6 MB bioconda
      openssl-1.0.2p | h470a237_0 3.5 MB conda-forge
      ------------------------------------------------------------
      Total: 10.4 MB

      The following NEW packages will be INSTALLED:

      goleft: 0.1.18-1 bioconda

      The following packages will be UPDATED:

      ca-certificates: 2018.8.13-ha4d7672_0 conda-forge --> 2018.8.24-ha4d7672_0 conda-forge
      certifi: 2018.8.13-py36_0 conda-forge --> 2018.8.24-py36_1 conda-forge
      openssl: 1.0.2o-h470a237_1 conda-forge --> 1.0.2p-h470a237_0 conda-forge

      Proceed ([y]/n)? Y


      Downloading and Extracting Packages
      ca-certificates-2018 | 136 KB | ####################################################################################################################### | 100%
      certifi-2018.8.24 | 139 KB | ####################################################################################################################### | 100%
      goleft-0.1.18 | 6.6 MB | ####################################################################################################################### | 100%
      openssl-1.0.2p | 3.5 MB | ####################################################################################################################### | 100%
      Preparing transaction: done
      Verifying transaction: done
      Executing transaction: done

  • Jit posted to the wire 2280 days ago
    #Multiline Fasta To #SingleLine Fasta $ awk '/^>/ {printf("\n%s\n",$0);next; } { printf("%s",$0);} END {printf("\n");}' < file.fa
  • Rahul Nayak created a page Benchmarking Perl Module ! in the group Perl *PIPERs 2283 days ago
    The benchmark module is a great tool to know the time the code takes to run. The output is usually in terms of CPU time. This module provides us with a way to optimize our code. With the advent of petascale computing and other multicore processor it...
    Comments
    • BioStar 618 days ago

      Benchmarking a Perl module involves measuring the performance of the module in terms of its execution time and memory usage. This can be done using the Perl Benchmark module, which provides a simple and standardized way to measure and compare the performance of Perl code.

      Here is a quick guide to benchmarking a Perl module using the Benchmark module:

      1. Install the Benchmark module: If you don't already have the Benchmark module installed, you can install it using the following command:

        cpan Benchmark

      2. Write benchmark code: Write a simple benchmark program that exercises the functionality of your Perl module. This program should take the form of a subroutine that runs the code you want to benchmark. Here's an example of a benchmark subroutine that calls a function from a hypothetical module named "MyModule":

        use MyModule; use Benchmark qw(:hireswallclock); sub benchmark_my_module { my $result = MyModule::my_function(); }
      3. Run the benchmark: Call the timethese function from the Benchmark module to run the benchmark. The timethese function takes two arguments: the number of iterations to run and a reference to the benchmark subroutine. Here's an example of how to call the timethese function to run the benchmark for 100 iterations:

        timethese(100, { 'MyModule' => \&benchmark_my_module, });
      4. Analyze the results: The timethese function will output the results of the benchmark, including the number of iterations, the total time taken, and the average time per iteration. You can use these results to compare the performance of your Perl module to other modules or to previous versions of your own module. You can also use other functions from the Benchmark module, such as cmpthese, to compare the performance of multiple modules or subroutines.

      In summary, benchmarking a Perl module involves writing a benchmark program that exercises the functionality of the module, running the benchmark using the timethese function from the Benchmark module, and analyzing the results to compare the performance of the module. The Benchmark module provides a simple and standardized way to measure and compare the performance of Perl code.

  • Rahul Nayak created a page Parallel Processing with Perl ! 2283 days ago
    Here is a small tutorial on how to make best use of multiple processors for bioinformatics analysis. One best way is using perl threads and forks. Knowing how these threads and forks work is very important before implementing them. Getting to know...
  • Bioinformatics jobs in Spain http://genome.crg.es/main/joboffers.php