https://bioinformaticsonline.com/snippets/owner/lege?offset=0 https://bioinformaticsonline.com/snippets/view/45197/onliner-to-convert-minimap2-to-paf Wed, 03 Jun 2026 07:03:26 -0500 https://bioinformaticsonline.com/snippets/view/45197/onliner-to-convert-minimap2-to-paf awk -v OFS="\t" -v ref_species="species1" -v query_species="species2" '{ print $6, $8, $9, $1, $3, $4, $5, ref_species, query_species }' mypaf.paf > synPlotter.tsv]]> LEGE https://bioinformaticsonline.com/snippets/view/44753/python-script-to-split-a-dna-sequence-into-words-of-varying-lengths Thu, 02 Jan 2025 11:31:22 -0600 https://bioinformaticsonline.com/snippets/view/44753/python-script-to-split-a-dna-sequence-into-words-of-varying-lengths # Script to split a DNA sequence into words of varying lengths def split_dna_into_words(dna_sequence, min_length, max_length): """ Splits a DNA sequence into words of lengths ranging from min_length to max_length. Parameters: dna_sequence (str): The DNA sequence to split (e.g., "ATGCGTAC"). min_length (int): The minimum length of each word. max_length (int): The maximum length of each word. Returns: dict: A dictionary where keys are word lengths and values are lists of DNA words of that length. """ if not dna_sequence: raise ValueError("The DNA sequence cannot be empty.") if min_length <= 0 or max_length <= 0: raise ValueError("Word lengths must be positive integers.") if min_length > max_length: raise ValueError("Minimum length cannot be greater than maximum length.") # Ensure the DNA sequence contains valid nucleotides for nucleotide in dna_sequence: if nucleotide.upper() not in "ATCG": raise ValueError(f"Invalid character '{nucleotide}' found in DNA sequence.") # Generate words of varying lengths words_by_length = {} for length in range(min_length, max_length + 1): words_by_length[length] = [dna_sequence[i:i+length] for i in range(0, len(dna_sequence) - length + 1)] return words_by_length # Example usage def main(): dna_sequence = "ATGCGTACGCTAATGCGTACGCTAATGCGTACGCTAATGCGTACGCTAATGCGTACGCTAATGCGTACGCTAATGCGTACGCTAATGCGTACGCTAATGCGTACGCTAATGCGTACGCTA" min_length = 3 max_length = 99 try: words_by_length = split_dna_into_words(dna_sequence, min_length, max_length) for length, words in words_by_length.items(): print(f"Words of length {length}:", words) except ValueError as e: print("Error:", e) if __name__ == "__main__": main()]]> LEGE https://bioinformaticsonline.com/snippets/view/44740/python-script-to-find-all-possible-repeats-in-a-dna-string Mon, 16 Dec 2024 07:54:38 -0600 https://bioinformaticsonline.com/snippets/view/44740/python-script-to-find-all-possible-repeats-in-a-dna-string from collections import defaultdict def find_repeats_in_genome(genome, min_length=2, max_length=None): """ Finds all repeating sequences in a genome within a specified length range. Parameters: genome (str): The genome sequence. min_length (int): Minimum length of repeats to scan for (default: 2). max_length (int): Maximum length of repeats to scan for (default: None, meaning entire genome). Returns: dict: A dictionary where keys are repeating sequences and values are lists of starting positions. """ if max_length is None: max_length = len(genome) repeats = defaultdict(list) # Iterate over all possible lengths of substrings for length in range(min_length, max_length + 1): seen = defaultdict(list) # Tracks occurrences of substrings of the current length # Sliding window approach for i in range(len(genome) - length + 1): substring = genome[i:i + length] seen[substring].append(i) # Filter substrings that appear more than once for substring, positions in seen.items(): if len(positions) > 1: repeats[substring].extend(positions) return repeats # Example usage def main(): genome = "ATCGATCGAATTCGATCG" # Example genome sequence min_length = 2 max_length = 5 repeats = find_repeats_in_genome(genome, min_length, max_length) print("Repeating sequences:") for seq, positions in repeats.items(): print(f"Sequence: {seq}, Positions: {positions}") if __name__ == "__main__": main()]]> LEGE https://bioinformaticsonline.com/snippets/view/44738/python-script-for-treemap-using-pythons-plotly-library Sat, 14 Dec 2024 12:45:15 -0600 https://bioinformaticsonline.com/snippets/view/44738/python-script-for-treemap-using-pythons-plotly-library import plotly.express as px import pandas as pd # Sample dataset: Representing biological pathways and their associated counts data = { "Category": ["Metabolism", "Metabolism", "Metabolism", "Cellular Processes", "Cellular Processes", "Cellular Processes", "Information Storage", "Information Storage"], "Subcategory": ["Carbohydrate metabolism", "Lipid metabolism", "Amino acid metabolism", "Signal transduction", "Cell cycle", "Transport", "DNA replication", "RNA processing"], "Count": [150, 120, 90, 100, 85, 70, 110, 95] } # Convert data to a DataFrame df = pd.DataFrame(data) # Create the treemap fig = px.treemap( df, path=["Category", "Subcategory"], # Hierarchical levels values="Count", # Size of the treemap blocks color="Count", # Color based on the count values color_continuous_scale="Viridis" # Color scale ) # Add a title fig.update_layout(title="Treemap: Hierarchical Data Representation in Bioinformatics") # Show the plot fig.show()]]> LEGE https://bioinformaticsonline.com/snippets/view/44733/bacterial-comparative-genomics-pipeline-bash-script Sat, 14 Dec 2024 12:34:57 -0600 https://bioinformaticsonline.com/snippets/view/44733/bacterial-comparative-genomics-pipeline-bash-script #!/bin/bash # Bacterial Comparative Genomics Pipeline Script # This script automates key steps in bacterial comparative genomics using popular bioinformatics tools. # Ensure the script stops on error set -e # Define paths WORKDIR="./bacterial_genomics_pipeline" INPUT_FASTA_DIR="./input_genomes" OUTPUT_DIR="./output" CORE_PAN_DIR="$OUTPUT_DIR/core_pan_analysis" PHYLOGENY_DIR="$OUTPUT_DIR/phylogeny" ALIGNMENT_DIR="$OUTPUT_DIR/genome_alignment" RESISTANCE_DIR="$OUTPUT_DIR/antibiotic_resistance" SYNTENY_DIR="$OUTPUT_DIR/synteny_analysis" # Create directories if they do not exist mkdir -p $WORKDIR $OUTPUT_DIR $CORE_PAN_DIR $PHYLOGENY_DIR $ALIGNMENT_DIR $RESISTANCE_DIR $SYNTENY_DIR # Tools required PROKKA="prokka" ROARY="roary" MAUVE="progressiveMauve" IQTREE="iqtree" ABRICATE="abricate" MCSCANX="mcscanx" # Step 1: Genome Annotation using Prokka annotate_genomes() { echo "\n=== Annotating Genomes with Prokka ===" for fasta in $INPUT_FASTA_DIR/*.fasta; do basename=$(basename $fasta .fasta) output_path="$OUTPUT_DIR/annotation_$basename" echo "Annotating $basename..." $PROKKA --outdir $output_path --prefix $basename $fasta done } # Step 2: Core and Pan-genome Analysis using Roary core_pan_analysis() { echo "\n=== Performing Core and Pan-genome Analysis with Roary ===" gff_files=$(find $OUTPUT_DIR -name "*.gff") roary_output="$CORE_PAN_DIR/pan_genome_analysis" mkdir -p $roary_output $ROARY -e -n -v -p 8 -o $roary_output $gff_files } # Step 3: Whole Genome Alignment using Mauve align_genomes() { echo "\n=== Aligning Genomes with Mauve ===" alignment_output="$ALIGNMENT_DIR/aligned_genomes.xmfa" echo "Running Mauve on input genomes..." $MAUVE --output=$alignment_output $(find $INPUT_FASTA_DIR -name "*.fasta") echo "Alignment saved to $alignment_output" } # Step 4: Phylogenetic Tree Construction using IQ-TREE construct_phylogeny() { echo "\n=== Constructing Phylogenetic Tree with IQ-TREE ===" alignment="$ALIGNMENT_DIR/aligned_genomes.xmfa" phylo_output="$PHYLOGENY_DIR/phylogeny_tree" iqtree_output="$phylo_output.treefile" echo "Running IQ-TREE on aligned genomes..." $IQTREE -s $alignment -m GTR+G -nt AUTO -pre $phylo_output echo "Phylogenetic tree saved to $iqtree_output" } # Step 5: Antibiotic Resistance Gene Identification using ABRicate identify_resistance_genes() { echo "\n=== Identifying Antibiotic Resistance Genes with ABRicate ===" for fasta in $INPUT_FASTA_DIR/*.fasta; do basename=$(basename $fasta .fasta) output_path="$RESISTANCE_DIR/${basename}_resistance.txt" echo "Analyzing $basename for resistance genes..." abricate $fasta > $output_path done } # Step 6: Synteny Analysis using MCScanX synteny_analysis() { echo "\n=== Performing Synteny Analysis with MCScanX ===" synteny_output="$SYNTENY_DIR/synteny_results" mkdir -p $synteny_output echo "Running MCScanX on annotated genomes..." MCScanX $OUTPUT_DIR > "$synteny_output/results.txt" echo "Synteny analysis results saved to $synteny_output" } # Main workflow annotate_genomes core_pan_analysis align_genomes construct_phylogeny identify_resistance_genes synteny_analysis echo "\n=== Bacterial Comparative Genomics Pipeline Complete ===" echo "Results saved in $OUTPUT_DIR"]]> LEGE https://bioinformaticsonline.com/snippets/view/44701/methods-to-upgrade-the-ubuntu Fri, 06 Dec 2024 23:36:11 -0600 https://bioinformaticsonline.com/snippets/view/44701/methods-to-upgrade-the-ubuntu #Install ubuntu-release-upgrader-core if it is not already installed: sudo apt-get install ubuntu-release-upgrader-core #Edit /etc/update-manager/release-upgrades and set Prompt=normal #Launch the upgrade tool: do-release-upgrade #Follow the on-screen instructions.]]> LEGE https://bioinformaticsonline.com/snippets/view/44671/install-edirect Thu, 03 Oct 2024 01:52:15 -0500 https://bioinformaticsonline.com/snippets/view/44671/install-edirect sh -c "$(curl -fsSL https://ftp.ncbi.nlm.nih.gov/entrez/entrezdirect/install-edirect.sh)"]]> LEGE https://bioinformaticsonline.com/snippets/view/44670/extract-the-fasta-sequence-using-ids Thu, 03 Oct 2024 01:27:32 -0500 https://bioinformaticsonline.com/snippets/view/44670/extract-the-fasta-sequence-using-ids #Extract sequences with names in file name.list, one sequence name per line: seqtk subseq input.fasta name.list > output.fasta]]> LEGE https://bioinformaticsonline.com/snippets/view/44665/r-script-to-add-p-values-in-plots Tue, 17 Sep 2024 20:23:02 -0500 https://bioinformaticsonline.com/snippets/view/44665/r-script-to-add-p-values-in-plots library(ggplot2) library(tidyverse) library(ggpubr) my_comp <- list( c("0.5", "1"), c("1", "2"), c("0.5", "2") ) ggboxplot(ToothGrowth, x = "dose", y = "len", fill = "dose", palette = "Dark2")+ stat_compare_means(label = "p.format", comparisons = my_comp, method = "t.test", symnum.args = list(cutpoints = c(0, 0.001, 1), symbols = "p < 0.001"))]]> LEGE https://bioinformaticsonline.com/snippets/view/44532/commands-to-create-conda-env Mon, 13 May 2024 06:38:11 -0500 https://bioinformaticsonline.com/snippets/view/44532/commands-to-create-conda-env (base) [lege@hn1 testVisanu]$ conda create -n pythonENV python=3.10 scipy=1.13.0 astroid babel Channels: - conda-forge - bioconda - defaults Platform: linux-64 Collecting package metadata (repodata.json): done Solving environment: done ==> WARNING: A newer version of conda exists. <== current version: 24.3.0 latest version: 24.4.0 Please update conda by running $ conda update -n base -c conda-forge conda ## Package Plan ## environment location: /home/lege/miniforge3/envs/pythonENV added / updated specs: - astroid - babel - python=3.10 - scipy=1.13.0 The following packages will be downloaded: package | build ---------------------------|----------------- astroid-3.2.0 | py310hff52083_0 389 KB conda-forge babel-2.14.0 | pyhd8ed1ab_0 7.3 MB conda-forge libblas-3.9.0 |22_linux64_openblas 14 KB conda-forge libcblas-3.9.0 |22_linux64_openblas 14 KB conda-forge libgfortran-ng-13.2.0 | h69a702a_7 24 KB conda-forge libgfortran5-13.2.0 | hca663fb_7 1.4 MB conda-forge liblapack-3.9.0 |22_linux64_openblas 14 KB conda-forge libopenblas-0.3.27 |pthreads_h413a1c8_0 5.3 MB conda-forge numpy-1.26.4 | py310hb13e2d6_0 6.7 MB conda-forge pytz-2024.1 | pyhd8ed1ab_0 184 KB conda-forge scipy-1.13.0 | py310h93e2701_1 15.8 MB conda-forge typing-extensions-4.11.0 | hd8ed1ab_0 10 KB conda-forge typing_extensions-4.11.0 | pyha770c72_0 37 KB conda-forge ------------------------------------------------------------ Total: 37.1 MB The following NEW packages will be INSTALLED: _libgcc_mutex conda-forge/linux-64::_libgcc_mutex-0.1-conda_forge _openmp_mutex conda-forge/linux-64::_openmp_mutex-4.5-2_gnu astroid conda-forge/linux-64::astroid-3.2.0-py310hff52083_0 babel conda-forge/noarch::babel-2.14.0-pyhd8ed1ab_0 bzip2 conda-forge/linux-64::bzip2-1.0.8-hd590300_5 ca-certificates conda-forge/linux-64::ca-certificates-2024.2.2-hbcca054_0 ld_impl_linux-64 conda-forge/linux-64::ld_impl_linux-64-2.40-h55db66e_0 libblas conda-forge/linux-64::libblas-3.9.0-22_linux64_openblas libcblas conda-forge/linux-64::libcblas-3.9.0-22_linux64_openblas libffi conda-forge/linux-64::libffi-3.4.2-h7f98852_5 libgcc-ng conda-forge/linux-64::libgcc-ng-13.2.0-h77fa898_7 libgfortran-ng conda-forge/linux-64::libgfortran-ng-13.2.0-h69a702a_7 libgfortran5 conda-forge/linux-64::libgfortran5-13.2.0-hca663fb_7 libgomp conda-forge/linux-64::libgomp-13.2.0-h77fa898_7 liblapack conda-forge/linux-64::liblapack-3.9.0-22_linux64_openblas libnsl conda-forge/linux-64::libnsl-2.0.1-hd590300_0 libopenblas conda-forge/linux-64::libopenblas-0.3.27-pthreads_h413a1c8_0 libsqlite conda-forge/linux-64::libsqlite-3.45.3-h2797004_0 libstdcxx-ng conda-forge/linux-64::libstdcxx-ng-13.2.0-hc0a3c3a_7 libuuid conda-forge/linux-64::libuuid-2.38.1-h0b41bf4_0 libxcrypt conda-forge/linux-64::libxcrypt-4.4.36-hd590300_1 libzlib conda-forge/linux-64::libzlib-1.2.13-hd590300_5 ncurses conda-forge/linux-64::ncurses-6.5-h59595ed_0 numpy conda-forge/linux-64::numpy-1.26.4-py310hb13e2d6_0 openssl conda-forge/linux-64::openssl-3.3.0-hd590300_0 pip conda-forge/noarch::pip-24.0-pyhd8ed1ab_0 python conda-forge/linux-64::python-3.10.14-hd12c33a_0_cpython python_abi conda-forge/linux-64::python_abi-3.10-4_cp310 pytz conda-forge/noarch::pytz-2024.1-pyhd8ed1ab_0 readline conda-forge/linux-64::readline-8.2-h8228510_1 scipy conda-forge/linux-64::scipy-1.13.0-py310h93e2701_1 setuptools conda-forge/noarch::setuptools-69.5.1-pyhd8ed1ab_0 tk conda-forge/linux-64::tk-8.6.13-noxft_h4845f30_101 typing-extensions conda-forge/noarch::typing-extensions-4.11.0-hd8ed1ab_0 typing_extensions conda-forge/noarch::typing_extensions-4.11.0-pyha770c72_0 tzdata conda-forge/noarch::tzdata-2024a-h0c530f3_0 wheel conda-forge/noarch::wheel-0.43.0-pyhd8ed1ab_1 xz conda-forge/linux-64::xz-5.2.6-h166bdaf_0 Proceed ([y]/n)? y Downloading and Extracting Packages: Preparing transaction: done Verifying transaction: done Executing transaction: done # # To activate this environment, use # # $ conda activate pythonENV # # To deactivate an active environment, use # # $ conda deactivate]]> LEGE