Update on the best pipeline for sequencing?
2
2
Entering edit mode
7.5 years ago
apuhegde ▴ 20

It's been 6.4 years since this question was asked last:

What Is The Best Pipeline For Human Whole Exome Sequencing?

I have this same question but I see that 6.4 years ago people were of the opinion that a lot of the best practices were still under development and included quite a bit of of trial and error. I'm assuming things have improved now and the genomics/informatics community can probably point out some of the more popular/standard pipelines that are in use today. So I have the same question again:

What Is The Best Pipeline For Human Whole Exome Sequencing in 2016?

next-gen sequencing whole genome exome RNA-Seq • 1.7k views
ADD COMMENT
1
Entering edit mode

See these artiles to get the information:

VDAP-GUI: a user-friendly pipeline for variant discovery and annotation of raw next-generation sequencing data

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4754298/

MutAid: Sanger and NGS Based Integrated Pipeline for Mutation Identification, Validation and Annotation in Human Molecular Genetics

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4739551/

Evaluation of Next Generation Sequencing Platforms for Whole Exome Variant Analysis

http://www.omicsonline.org/open-access/evaluation-of-next-generation-sequencing-platforms-for-whole-exome-variant-analysis-2471-2663-1000112.pdf

This article below is from June 2015, but I don't think half a year really matters:

New insights into the performance of human whole-exome capture platforms

http://nar.oxfordjournals.org/content/early/2015/03/27/nar.gkv216.full

Development and validation of a whole-exome sequencing test for simultaneous detection of point mutations, indels and copy-number alterations for precision cancer care

http://www.nature.com/articles/npjgenmed201619

New tool mines whole-exome sequencing data to match cancer with best drug

https://www.sciencedaily.com/releases/2016/03/160329184959.htm

Unsolved challenges of clinical whole-exome sequencing: a systematic literature review of end-users’ views

https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-016-0213-6

Most advances are reported for new medical treatment.

ADD REPLY
3
Entering edit mode
7.5 years ago

I think the most commonly accepted pipeline is the "best practices" of gatk.

ADD COMMENT
0
Entering edit mode
7.5 years ago
ivivek_ngs ★ 5.2k

It all depends to the number of samples in question for which exome data is produced and what depth of coverage has they been subjected to.

Before any SNP calling is made thr processing of bam files is mostly done by gatk and I would still go by it. However if you do not have enough samples and you are also having medium depth in the lines of 70-80x then other algorithms should be used for the variant calls in this case. Plethora of tools are available.

Gatk works well with high depthand large number of samples but if you have less number of samples then it is advisable to use gatk for processing alignments but final call can be made on gatk processed aligned files with other variant callers.

If you are working in tumor and there are evidences that low infiltrating mutations might hamper the genome stability causing mutational aberrations that might lead to a tumoral evolution. I would go for something like Mutect2 in that case. Rest any tool that targets high frequency mutations can be used to call variants. I always preferred the marriage of gatk preprocessing followed with variant calling post processing the alignment with some targeted variant callers to provide much more reliable and true positive calls.

You can follow these papers

Paper one

Papers two

So be clear of what your experimental design is about and what is your intention to unravel and then go ahead . Good luck

ADD COMMENT

Login before adding your answer.

Traffic: 2739 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6