Skip to main content

An HPV integration sites detection tool for targeted capture sequencing data

Project description

Documentation Status License PyPI version

Host Downloads
PyPI Downloads

SearcHPV

An HPV integration point detection tool for targeted capture sequencing data

Introdution

  • SearcHPV detects HPV fusion sites on both human genome and HPV genome
  • SearcHPV is able to provide locally assembled contigs for each integration events. It will report at least one and at most two contigs for each integration sites. The two contigs will provide information captured for left and right sides of the event.

Getting started

  1. Required resources
  • Unix like environment
  • Third-party tools:
Python/3.7.3 https://www.python.org/downloads/release/python-373/
samtools/1.5 https://github.com/samtools/samtools/releases/tag/1.5
BWA/0.7.15-r1140 https://github.com/lh3/bwa/releases/tag/v0.7.15
java/1.8.0_252 https://www.oracle.com/java/technologies/javase/8all-relnotes.html
Picard Tools/2.23.8 https://github.com/broadinstitute/picard/releases/tag/2.23.8
PEAR/0.9.2 https://github.com/tseemann/PEAR
CAP3/02/10/15 http://seq.cs.iastate.edu/cap3.html

After intalling these tools, please make sure that their path have been added to you ".bashrc" script so that you can use them by typing the tool names in the terminal.

  1. Download and install Firstly, download and install the required resources. Then, tap these commands in your terminal:
pip install searcHPV

  1. Usage SearcHPV have four main steps. You could either run it start-to-finish or run it step-by-step.
  • Usage:
searcHPV <options> ...
  • Standard options:
 -fastq1 <str>  sequencing data: fastq/fq.gz file
 -fastq2 <str>  sequencing data: fastq/fq.gz file
 -humRef <str>  human reference genome: fasta file
 -virRef <str>  HPV reference genome: fasta file
  • Optional options:
-h, --help      show this help message and exit
-window <int>   the length of region searching for informative reads, default=300
-output <str>   output directory, default "./"
-alignment      run the alignment step, step1
-genomeFusion   call the genome fusion points, step2
-assemble local assemble for each integration event, step3
-hpvFusion call the HPV fusion points, step4

  • Examples:
  1. Run it start-to-finish:
searcHPV -fastq1 Sample_81279.R1.fastq.gz -fastq2 Sample_81279.R2.fastq.gz -humRef hs37d5.fa -virRef HPV.fa -output /home/scratch/HPV_fusion/Sample_81279

  1. Run it step-by-step:
searchHPV -align -fastq1 Sample_81279.R1.fastq.gz -fastq2 Sample_81279.R2.fastq.gz -humRef hs37d5.fa -virRef HPV.fa -output /home/scratch/HPV_fusion/Sample_81279
searchHPV -genomeFusion -fastq1 Sample_81279.R1.fastq.gz -fastq2 Sample_81279.R2.fastq.gz -humRef hs37d5.fa -virRef HPV.fa -output /home/scratch/HPV_fusion/Sample_81279
searchHPV -assemble -fastq1 Sample_81279.R1.fastq.gz -fastq2 Sample_81279.R2.fastq.gz -humRef hs37d5.fa -virRef HPV.fa -output /home/scratch/HPV_fusion/Sample_81279
searchHPV -hpvFusion -fastq1 Sample_81279.R1.fastq.gz -fastq2 Sample_81279.R2.fastq.gz -humRef hs37d5.fa -virRef HPV.fa -output /home/scratch/HPV_fusion/Sample_81279

Note: if run it step-by-step, please make sure the output directories for all steps are the same.

Output

  1. Alignment: the marked dupliaction alignment bam file and customized reference genome.\
  2. Genome Fusion Point Calling: orignal callset, filtered callset, filtered clustered callset.\
  3. Assemble: supportive reads, contigs for each integration events (unfiltered).\
  4. HPV fusion Point Calling: alignment bam file for contigs againt human and HPV genome.\ Final outputs are under the folder "call_fusion_virus": summary of all the integration events : "HPVfusionPointContig.txt" contig sequences for all the integration events: "ContigsSequence.fa"

Citation

SearcHPV: a novel approach to identify and assemble human papillomavirus-host genomic integration events in cancer --- Accepted by Cancer

Contact

wenjingu@umich.edu

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

searcHPV-1.0.9.11.tar.gz (22.3 kB view details)

Uploaded Source

Built Distributions

searcHPV-1.0.9.11-py3.8.egg (42.7 kB view details)

Uploaded Source

searcHPV-1.0.9.11-py3-none-any.whl (23.4 kB view details)

Uploaded Python 3

File details

Details for the file searcHPV-1.0.9.11.tar.gz.

File metadata

  • Download URL: searcHPV-1.0.9.11.tar.gz
  • Upload date:
  • Size: 22.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/3.10.0 pkginfo/1.8.2 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

File hashes

Hashes for searcHPV-1.0.9.11.tar.gz
Algorithm Hash digest
SHA256 003a11bedbc3268da4a31d65849a72b3004cbd6358cf8b942273763aac758345
MD5 6ab788adc4a929e26ced3e921d285790
BLAKE2b-256 7a97b3b9d27fb7f763d0e4c6a49c12fdcb637a39223b9dd437c170a9d1cc9d4b

See more details on using hashes here.

Provenance

File details

Details for the file searcHPV-1.0.9.11-py3.8.egg.

File metadata

  • Download URL: searcHPV-1.0.9.11-py3.8.egg
  • Upload date:
  • Size: 42.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/3.10.0 pkginfo/1.8.2 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

File hashes

Hashes for searcHPV-1.0.9.11-py3.8.egg
Algorithm Hash digest
SHA256 2d927212498aa5e17ce831c1880c0aa4cb915e2ec029e1a90d2d8f671c090816
MD5 5faa2d25a530f3ff9e86e2af584385fd
BLAKE2b-256 dbfec0c553410abb74437674981fcc3aa58e5e846c0bf8d6e85432c88b7a8331

See more details on using hashes here.

Provenance

File details

Details for the file searcHPV-1.0.9.11-py3-none-any.whl.

File metadata

  • Download URL: searcHPV-1.0.9.11-py3-none-any.whl
  • Upload date:
  • Size: 23.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/3.10.0 pkginfo/1.8.2 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

File hashes

Hashes for searcHPV-1.0.9.11-py3-none-any.whl
Algorithm Hash digest
SHA256 f8bf98221af56b5c13113b3e61e20f418acc1eb99f61cd1a69a8e9532e2994e2
MD5 8c9b8bc12996b0f73e6754d82e6fa91d
BLAKE2b-256 a0793bc9279c6d35dd1aa2ffbdb0d4704bb2942b92699e13d23c07e1a1555e4d

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page