Skip to main content

Not your grandma's NGS analysis - software for analyzing FASTQs from SRSLY libraries

Project description

ClaretBio's SRSLY Library processing software

This software is for the basic informatic processing of sequencing data generated using ClaretBio's SRSLY library prep kit with or without using UMIs.

Installation

This sofware can be installed as a python package using the command pip install srslyrun

Usage

The basic analysis can be run with srsly runsamples for standard libraries or srsly runsamples --umi for libraries with unique molecular identifiers (UMIs). This software takes in raw fastqs and trims adapters, aligns to a user-specified reference genome, and marks duplicates. For UMI aware demultiplexing of SRSLY libraries please use our SRSLYumi python package (more info at https://github.com/claretbio/SRSLYumi).

In order to run, this software requires an installation of conda- installation instructions can be found here.We recommend using mamba, which can be installed with conda install -n base -c conda-forge mamba once conda is installed. It can also be installed directly from

Required Arguments

`--reference` : a path to the reference genome you wish to align to (no default, this must be provided, and must be a file ending in `.fasta` or `.fa`)

`--libraries` or `--libfile`: the library IDs you would like analyzed in comma separated format and in a file with one id per line, respectively

Optional Arguments

`--fastqdir` : the directory containing the raw fastqs you wish to process (if not specified, defaults to current working directory)

`--resultsdir` : the directory you would like the output to be in (if not specified, defaults to current working directory)

The library IDs provided should match the beginning of the fastq files, for example the library ID for fastq files named lib1_R1.fastq.gz and lib1_R2.fastq.gz would be lib1. This can be provided directly on the command line with a comma separated list like --libraries lib1,lib2 or as a file that lists one library ID per line with --libfile libfile.txt.

an example command:

srsly runsamples --fastqdir /home/user/fastqfiles --resultsdir /home/user/srslyanalysis --reference /home/user/genomes/hg19.fa --libraries lib1,lib2,lib3

For reproducibility's sake and to ensure appropriate versions we use snakemake wrappers for many of the tools in this pipeline, which are often slow to create the first time they are used. As a result, your first time running the software may take a long time - don't worry, this is totally normal!

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

srslyrun-0.2.1.tar.gz (13.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

srslyrun-0.2.1-py3-none-any.whl (11.9 kB view details)

Uploaded Python 3

File details

Details for the file srslyrun-0.2.1.tar.gz.

File metadata

  • Download URL: srslyrun-0.2.1.tar.gz
  • Upload date:
  • Size: 13.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for srslyrun-0.2.1.tar.gz
Algorithm Hash digest
SHA256 34ce1533ebaaf67abbf409173d76809effb6a82df9809d2d1231c05d288fa2bb
MD5 f03755e98577e55217a648f5b172e6f5
BLAKE2b-256 dd8529f758e43aff470bcb373f2726136affee97f7733fad086a358787a0eeef

See more details on using hashes here.

File details

Details for the file srslyrun-0.2.1-py3-none-any.whl.

File metadata

  • Download URL: srslyrun-0.2.1-py3-none-any.whl
  • Upload date:
  • Size: 11.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for srslyrun-0.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 3bd24f32c198fb956db602a71aae1024128b6676453b7118c42a3e4ca641f675
MD5 82b2ae6dd79143039110035e7126ed92
BLAKE2b-256 4c43f5e7487e154329f93c0a939293c51edb0b51dfe735df99a067c71bd70c20

See more details on using hashes here.

Supported by

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