BOL: Related items

Biological databases !

BioStar — Wed, 12 Feb 2020 01:16:29 -0600

Now a days there are a lots of genomics databases available around the world. This bookmark is created to provide all links in one place ...

ftp://ftp.ncbi.nih.gov/genomes/

https://hgdownload.soe.ucsc.edu/downloads.html

Address of the bookmark: ftp://ftp.ncbi.nih.gov/genomes/

Find certain files/documents in Linux OS

Rahul Nayak — Sun, 06 Apr 2014 23:56:18 -0500

As bioinformatician I know the fact that we usually handle the large dataset and lost in the huge numbers of files and folders. In order to search the missing file a strong search command is required. The Linux Find Command is one of the most important and much used command in Linux sytems. Find command used to search and locate list of files and directories based on conditions you specify for files that match the arguments. Find can be used in variety of conditions like you can find files by permissions, users, groups, file type, date, size and other possible criteria.

Through this article we are sharing our day-to-day Linux find command experience and its usage in the form of examples. In this article we will show you the most used 35 Find Commands examples in Linux. We have divided the section into Five parts from basic to advance usage of find command.

Part I – Basic Find Commands for Finding Files with Names
1. Find Files Using Name in Current Directory

Find all the files whose name is gene.txt in a current working directory.

# find . -name gene.txt

./gene.txt

2. Find Files Under Home Directory

Find all the files under /home directory with name gene.txt.

# find /home -name gene.txt

/home/gene.txt

3. Find Files Using Name and Ignoring Case

Find all the files whose name is gene.txt and contains both capital and small letters in /home directory.

# find /home -iname gene.txt

./gene.txt
./Gene.txt

4. Find Directories Using Name

Find all directories whose name is Gene in / directory.

# find / -type d -name Gene

/Gene

5. Find fasta Files Using Name

Find all php files whose name is gene.fasta in a current working directory.

# find . -type f -name gene.fasta

./gene.fasta

6. Find all PHP Files in Directory

Find all fasta files in a directory.

# find . -type f -name "*.fasta"

./gene.fasta
./cancer.fasta
./allgene.fasta

Part II – Find Files Based on their Permissions
7. Find Files With 777 Permissions

Find all the files whose permissions are 777.

# find . -type f -perm 0777 -print

8. Find Files Without 777 Permissions

Find all the files without permission 777.

# find / -type f ! -perm 777

9. Find SGID Files with 644 Permissions

Find all the SGID bit files whose permissions set to 644.

# find / -perm 2644

10. Find Sticky Bit Files with 551 Permissions

Find all the Sticky Bit set files whose permission are 551.

# find / -perm 1551

11. Find SUID Files

Find all SUID set files.

# find / -perm /u=s

12. Find SGID Files

Find all SGID set files.

# find / -perm /g+s

13. Find Read Only Files

Find all Read Only files.

# find / -perm /u=r

14. Find Executable Files

Find all Executable files.

# find / -perm /a=x

15. Find Files with 777 Permissions and Chmod to 644

Find all 777 permission files and use chmod command to set permissions to 644.

# find / -type f -perm 0777 -print -exec chmod 644 {} \;

16. Find Directories with 777 Permissions and Chmod to 755

Find all 777 permission directories and use chmod command to set permissions to 755.

# find / -type d -perm 777 -print -exec chmod 755 {} \;

17. Find and remove single File

To find a single file called gene.txt and remove it.

# find . -type f -name "gene.txt" -exec rm -f {} \;

18. Find and remove Multiple File

To find and remove multiple files such as .fa or .gb, then use.

# find . -type f -name "*.fa" -exec rm -f {} \;

OR

# find . -type f -name "*.gb" -exec rm -f {} \;

19. Find all Empty Files

To file all empty files under certain path.

# find /tmp -type f -empty

20. Find all Empty Directories

To file all empty directories under certain path.

# find /tmp -type d -empty

21. File all Hidden Files

To find all hidden files, use below command.

# find /tmp -type f -name ".*"

Part III – Search Files Based On Owners and Groups
22. Find Single File Based on User

To find all or single file called gene.txt under / root directory of owner root.

# find / -user root -name gene.txt

23. Find all Files Based on User

To find all files that belongs to user Rahul under /home directory.

# find /home -user rahul

24. Find all Files Based on Group

To find all files that belongs to group Developer under /home directory.

# find /home -group developer

25. Find Particular Files of User

To find all .txt files of user Rahul under /home directory.

# find /home -user rahul -iname "*.txt"

Part IV – Find Files and Directories Based on Date and Time
26. Find Last 50 Days Modified Files

To find all the files which are modified 50 days back.

# find / -mtime 50

27. Find Last 50 Days Accessed Files

To find all the files which are accessed 50 days back.

# find / -atime 50

28. Find Last 50-100 Days Modified Files

To find all the files which are modified more than 50 days back and less than 100 days.

# find / -mtime +50 –mtime -100

29. Find Changed Files in Last 1 Hour

To find all the files which are changed in last 1 hour.

# find / -cmin -60

30. Find Modified Files in Last 1 Hour

To find all the files which are modified in last 1 hour.

# find / -mmin -60

31. Find Accessed Files in Last 1 Hour

To find all the files which are accessed in last 1 hour.

# find / -amin -60

Part V – Find Files and Directories Based on Size
32. Find 50MB Files

To find all 50MB files, use.

# find / -size 50M

33. Find Size between 50MB – 100MB

To find all the files which are greater than 50MB and less than 100MB.

# find / -size +50M -size -100M

34. Find and Delete 100MB Files

To find all 100MB files and delete them using one single command.

# find / -size +100M -exec rm -rf {} \;

35. Find Specific Files and Delete

Find all .gb files with more than 10MB and delete them using one single command.

# find / -type f -name *.gb -size +10M -exec rm {} \;

WAAFLE: a Workflow to Annotate Assemblies and Find LGT Events.

Neel — Thu, 23 Sep 2021 14:31:06 -0500

Lateral gene transfer (LGT) is an important mechanism for genome diversification in microbial communities, including the human microbiome. While methods exist to identify LGTs from sequenced isolate genomes, identifying LGTs from community metagenomes remains an open problem. To address this, we developed WAAFLE: a Workflow to Annotate Assemblies and Find LGT Events.

Address of the bookmark: http://huttenhower.sph.harvard.edu/waafle

Interesting Bioinformatics Resources !

Abhi — Fri, 11 Nov 2022 06:30:46 -0600

1. a reproducible workflow. https://www.youtube.com/watch?v=s3JldKoA0zw This two minute video will change your mind on reproducible research

2. Parallel sequencing lives, or what makes large sequencing projects successful https://academic.oup.com/gigascience/article/6/11/gix100/4557140?login=false

3. Common-sense approaches to sharing tabular data alongside publication https://www.sciencedirect.com/science/article/pii/S2666389921002300

4. A Reproducible Data Analysis Workflow with R Markdown, Git, Make, and Docker https://psyarxiv.com/8xzqy/

5. Practical Computational Reproducibility in the Life Sciences https://www.cell.com/cell-systems/fulltext/S2405-4712(18)30140-6

6. A video by Dr.Keith A. Baggerly from MD Anderson [The Importance of Reproducible Research in High-Throughput Biology](https://www.youtube.com/watch?v=7gYIs7uYbMo) highly recommended.

7. Ten Simple Rules for Reproducible Computational Research http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003285)

8. Good Enough Practices in Scientific Computing http://arxiv.org/abs/1609.00037

9. Best Practices for Scientific Computing https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001745

10. A Quick Guide to Organizing Computational Biology Projects http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.100042 A must read for computational biologists!

11. Reproducibility of computational workflows is automated using continuous analysis https://www.nature.com/articles/nbt.3780

12. Five selfish reasons to work reproducibly https://genomebiology.biomedcentral.com/articles/10.1186/s13059-015-0850-7

LRCstats: a tool for evaluating long reads correction methods

Aaryan Lokwani — Wed, 22 Aug 2018 11:05:04 -0500

LRCstats is an open-source pipeline for benchmarking DNA long read correction algorithms for long reads outputted by third generation sequencing technology such as machines produced by Pacific Biosciences. The reads produced by third generation sequencing technology, as the name suggests, are longer in length than reads produced by next generation sequencing technologies, such as those produced by Illumina. However, long reads are plagued by high error rates, which can cause issues in downstream analysis. Long read correction algorithms reduce the error rate of long reads either through self-correcting methods or using accurate, short reads outputted by next generation sequencing technologies to correct long reads.

Address of the bookmark: https://github.com/cchauve/lrcstats

Steps to find all the repeats in the genome !

Neel — Thu, 31 Aug 2023 02:43:28 -0500

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:

Install RepeatMasker: First, you need to install RepeatMasker on your system. You can download it from the RepeatMasker website[0].

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 -nolow -norna -no_is -div -lib RepeatMaskerLib.embl -gff -xsmall -small -poly -species -dir -length - genome.fasta

Replace the following placeholders with appropriate values:

: The number of processors/threads you want to use for parallel processing.
: The divergence value for the species you are analyzing. You can find divergence values for different species in the RepeatMasker documentation[0].
: The name of the species you are analyzing.
: The directory where you want the output files to be saved.
and : The minimum and maximum lengths of the repeats you want to find (in this case, 2 and 9).

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.

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 --length

Replace with the path to your RepeatMasker .out file, and 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.

S-plot2: Rapid Visual and Statistical Analysis of Genomic Sequences

Abhimanyu Singh — Tue, 02 Oct 2018 17:57:27 -0500

S-plot2 creates an interactive, two-dimensional heatmap capturing the similarities and dissimilarities in nucleotide usage between genomic sequences (partial or complete). In S-plot2, whole eukaryotic chromosomes and smaller prokaryotic genomes can be efficiently compared. The tool includes functionality to extract, analyze, and automate BLAST queries of regions of interest within the heatmap. This facilitates the investigation of quickly evolving coding regions, novel coding regions, and laterally transferred elements.

Address of the bookmark: https://bitbucket.org/lkalesinskas/splot

Predict Gene Ontology with sequences !

LEGE — Wed, 08 Jul 2020 04:59:28 -0500

PANNZER (Protein ANNotation with Z-scoRE) is a fully automated service for functional annotation of prokaryotic and eukaryotic proteins of unknown function. The tool is designed to predict the functional description (DE) and GO classes.

PANNZER2 processes bacterial proteomes in minutes and eukaryotic proteomes in an hour. You can use AAI-profiler to summarize a proteome's species neighbors and reveal taxonomic identity or contamination.

http://ekhidna2.biocenter.helsinki.fi/sanspanz/

IterPro is for the beginners

h ttps://www.ebi.ac.uk/interpro/

You can find other comparative info at https://academic.oup.com/view-large/118391389

Address of the bookmark: http://ekhidna2.biocenter.helsinki.fi/sanspanz/

minimap2: A versatile pairwise aligner for genomic and spliced nucleotide sequences

Jit — Wed, 20 Jun 2018 07:55:29 -0500

git clone https://github.com/lh3/minimap2 cd minimap2 && make # long sequences against a reference genome ./minimap2 -a test/MT-human.fa test/MT-orang.fa > test.sam # create an index first and then map ./minimap2 -d MT-human.mmi test/MT-human.fa ./minimap2 -a MT-human.mmi test/MT-orang.fa > test.sam # use presets (no test data) ./minimap2 -ax map-pb ref.fa pacbio.fq.gz > aln.sam # PacBio genomic reads ./minimap2 -ax map-ont ref.fa ont.fq.gz > aln.sam # Oxford Nanopore genomic reads ./minimap2 -ax sr ref.fa read1.fa read2.fa > aln.sam # short genomic paired-end reads ./minimap2 -ax splice ref.fa rna-reads.fa > aln.sam # spliced long reads ./minimap2 -ax splice -k14 -uf ref.fa reads.fa > aln.sam # Nanopore Direct RNA-seq ./minimap2 -cx asm5 asm1.fa asm2.fa > aln.paf # intra-species asm-to-asm alignment ./minimap2 -x ava-pb reads.fa reads.fa > overlaps.paf # PacBio read overlap ./minimap2 -x ava-ont reads.fa reads.fa > overlaps.paf # Nanopore read overlap # man page for detailed command line options man ./minimap2.1

Address of the bookmark: https://github.com/lh3/minimap2

COSINE: non-seeding method for mapping long noisy sequences

Jit — Fri, 26 Oct 2018 00:41:59 -0500

Third generation sequencing (TGS) are highly promising technologies but the long and noisy reads from TGS are difficult to align using existing algorithms. Here, we present COSINE, a conceptually new method designed specifically for aligning long reads contaminated by a high level of errors.

Address of the bookmark: https://github.com/SUwonglab/COSINE