FACTERA protocols

View FACTERA computational protocol

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FACTERA specifications

Information


Unique identifier OMICS_05484
Name FACTERA
Alternative name Fusion And Chromosomal Translocation Enumeration and Recovery Algorithm
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input format BAM
Operating system Unix/Linux
Computer skills Advanced
Stability Stable
Maintained Yes

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  • person_outline Ash Alizadeh <>
  • person_outline Maximilian Diehn <>

Publication for Fusion And Chromosomal Translocation Enumeration and Recovery Algorithm

FACTERA in pipelines

 (3)
2016
PMCID: 5108598
PMID: 27877056
DOI: 10.2147/OTT.S117097

[…] aligner) aligner 0.7.10. local alignment optimization, variant calling, and annotation were performed with gatk 3.2. dna translocation analysis was performed by using both tophat2 and factera 1.4.3.,, of the selected 16 patients, 10 were male and 6 were female. their age ranged between 29 and 58 years, with an average age of 40 years (). the most common symptoms present in every […]

2015
PMCID: 4632085
PMID: 26530882
DOI: 10.1038/srep16129

[…] before base substitution detection. local alignment optimization and variant calling and annotation were performed using gatk 3.2. dna translocation analysis was performed using both tophat2 and factera 1.4.3., analysis was performed for patients’ characteristics between the mutation positive group and negative group and the percentage of mutation carriers in fnmtc group was compared […]

2015
PMCID: 4884996
PMID: 26789109
DOI: 10.18632/oncotarget.6671

[…] data were analyzed by gatk 3.2 (https://www.broadinstitute.org/gatk/) and dna translocation analysis was performed by using both tophat2 (https://ccb.jhu.edu/software/tophat/index.shtml) and factera 1.4.3 ((http://factera.stanford.edu) []., differences of patient characteristics and clinicopathologic factors in the two-dimensional cross-comparison were evaluated statistically […]


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FACTERA in publications

 (15)
PMCID: 5951221
PMID: 29780256
DOI: 10.2147/OTT.S155995

[…] optimization, mark duplication, and variant calling were performed using genome analysis toolkit 3.2, picard (http://picard.sourceforge.net/), and varscan. gene rearrangements were called with fusion and chromosomal translocation enumeration and recovery algorithm (factera), and copy number variation was analyzed with an in-house algorithm based on sequencing depth. variants were filtered […]

PMCID: 5921972
PMID: 29703253
DOI: 10.1186/s12885-018-4298-5

[…] genome data sets to remove common snps. mutations identified within the whole blood controls were subtracted to exclude germline mutations where applicable. structural variants were detected using factera with default parameters []. adtex (https://adtex.sourceforge.net) was used to identify copy number variations (cnvs) with default parameters. all the genetic alterations identified […]

PMCID: 5769570
PMID: 29391810
DOI: 10.2147/OTT.S154589

[…] local alignment optimization, variant calling, and annotation were performed using gatk 3.2, mutect, and varscan, respectively. dna translocation analysis was performed using both tophat2 and factera 1.4.3. gene-level copy number variation was assessed using a t-statistic after normalizing reads depth at each region by total reads number and region size, and correcting gc-bias using […]

PMCID: 5439955
PMID: 28542371
DOI: 10.1371/journal.pone.0178169

[…] of tumor vs. normal read depth for each exon and extracted all exons showing deviation from the expected ratio, that is, corresponding to more than one unit haploid copy number change. the software factera [] with the default settings was used to detect gene fusions and structural variants including deletion, duplication, inversion and translocation. circos plots that included tracks showing […]

PMCID: 5564799
PMID: 28591696
DOI: 10.18632/oncotarget.17917

[…] were annotated with annovar and snpeff v3.6. annotation database including the exac, 1000 genomes, dbsnp, esp6500si-v2, and cosmic. dna translocation analysis was performed using both tophat2 and factera 1.4.3. cnv were identified using in-house r scripts based on the coverage ratio of the capture intervals in tumor and normal samples. coverage depth data were corrected for the sequencing […]


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FACTERA institution(s)
Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA; Division of Oncology, Department of Medicine, Stanford University, Stanford, CA, USA; Department of Radiation Oncology, Stanford University, Stanford, CA, USA; Stanford Cancer Institute, Stanford University, Stanford, CA, USA
FACTERA funding source(s)
Supported by the Stanford Cancer Institute Genomics Initiative; the Doris Duke Charitable Foundation; the US Department of Defense (LCRP Promising Clinician Research Award; W81XWH-12-1-0498); the US National Institutes of Health Director’s New Innovator Award Program (1-DP2-CA186569); the Damon Runyon Cancer Research Foundation; the Lymphoma Research Foundation; the Gabrielle’s Angel Foundation; the Radiological Society of North America (RR1221); and the Thomas & Stacey Siebel Foundation.

FACTERA reviews

 (2)
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Anonymous user #1051's avatar image No country

Anonymous user #1051

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Desktop
very fast, intuitive, and precise tool. optimized for targeted capture data, but performance on RNA-Seq data reasonably good in my hands, though but not tested against other tools. addition of a paired mode (tumor/normal) option would be a nice feature.
Anonymous user #1050's avatar image No country

Anonymous user #1050

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Desktop
Much much better that existing tools, especially for targeted capture data from cancer. Needs for improved a little for BWA-MEM, but still great.