GS-Preprocess: Containerized GUIDE-seq Data Analysis Tools with Diverse Sequencer Compatibility
Abstract RNA-guided nucleases (e.g. CRISPR-Cas) are used in a breadth of clinical and basic scientific subfields for the investigation or modification of biological processes. While these modern platforms for site-specific DNA cleavage are highly accurate, some applications (e.g. gene editing therapeutics) cannot tolerate DNA breaks at off-target sites, even at low levels. Thus, it is critically important to determine the genome-wide targeting profile of candidate RNA-guided nucleases prior to use. GUIDE-seq is a high-quality, easy-to-execute molecular method that detects and quantifies off-target cleavage. However, this method may remain costly or inaccessible to some researchers due to its library sequencing and analysis protocols, which require a MiSeq platform that must be preprogramed for non-standard output. Here, we present GS-Preprocess, an open-source containerized software that can use standard raw data output (BCL file format) from any Illumina sequencer to create input for the Bioconductor GUIDEseq off-target profiling package. Single-command GS-Preprocess performs FASTQ demultiplexing, adapter trimming, alignment, and UMI reference construction, improving the ease and accessibility of the GUIDE-seq method for a wide range of researchers..
| Medienart: |
|
|---|
Preprint| Erscheinungsjahr: |
2020 |
|---|---|
| Erschienen: |
2020 |
| Enthalten in: |
bioRxiv.org - (2020) vom: 29. Jan. Zur Gesamtaufnahme - year:2020 |
|---|
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Rodríguez, Tomás C. [VerfasserIn] |
|---|
| Links: |
Volltext [kostenfrei] |
|---|
| doi: |
10.1101/2020.01.26.914861 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
XBI000713279 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | XBI000713279 | ||
| 003 | DE-627 | ||
| 005 | 20230429082022.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 200313s2020 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1101/2020.01.26.914861 |2 doi | |
| 035 | |a (DE-627)XBI000713279 | ||
| 035 | |a (DE-599)biorXiv10.1101/2020.01.26.914861 | ||
| 035 | |a (biorXiv)10.1101/2020.01.26.914861 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | |a 570 |q DE-84 | |
| 100 | 1 | |a Rodríguez, Tomás C. |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a GS-Preprocess: Containerized GUIDE-seq Data Analysis Tools with Diverse Sequencer Compatibility |
| 264 | 1 | |c 2020 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a Abstract RNA-guided nucleases (e.g. CRISPR-Cas) are used in a breadth of clinical and basic scientific subfields for the investigation or modification of biological processes. While these modern platforms for site-specific DNA cleavage are highly accurate, some applications (e.g. gene editing therapeutics) cannot tolerate DNA breaks at off-target sites, even at low levels. Thus, it is critically important to determine the genome-wide targeting profile of candidate RNA-guided nucleases prior to use. GUIDE-seq is a high-quality, easy-to-execute molecular method that detects and quantifies off-target cleavage. However, this method may remain costly or inaccessible to some researchers due to its library sequencing and analysis protocols, which require a MiSeq platform that must be preprogramed for non-standard output. Here, we present GS-Preprocess, an open-source containerized software that can use standard raw data output (BCL file format) from any Illumina sequencer to create input for the Bioconductor GUIDEseq off-target profiling package. Single-command GS-Preprocess performs FASTQ demultiplexing, adapter trimming, alignment, and UMI reference construction, improving the ease and accessibility of the GUIDE-seq method for a wide range of researchers. | ||
| 700 | 1 | |a Pratt, Henry E. |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, PengPeng |e verfasserin |4 aut | |
| 700 | 1 | |a Amrani, Nadia |e verfasserin |4 aut | |
| 700 | 1 | |a Zhu, Lihua Julie |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t bioRxiv.org |g (2020) vom: 29. Jan. |
| 773 | 1 | 8 | |g year:2020 |g day:29 |g month:01 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1101/2020.01.26.914861 |z kostenfrei |3 Volltext |
| 912 | |a GBV_XBI | ||
| 912 | |a SSG-OLC-PHA | ||
| 951 | |a AR | ||
| 952 | |j 2020 |b 29 |c 01 | ||
| 953 | |2 045F |a 570 | ||