Cited by 14

The DOI matches its Crossref record.

FACADE : a fast and sensitive algorithm for the segmentation and calling of high resolution array CGH data

Coe, Bradley P., Chari, Raj, MacAulay, Calum, Lam, Wan L.·2010·Nucleic Acids Research

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/nar/gkq548

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Gain of 7p and loss of 8p have previously been reported to occur specifically in EGFR-mutated adenocarcinomas.

    “While gain of 7p and loss of 8p have been previously reported to occur specifically in EGFR mutated adenocarcinomas16, 17, gain of 16p was a novel association.”

    From Integrative Genomic Analyses Identifies GGA2 as a Cooperative Driver of EGFR-Mediated Lung Tumorigenesis (2019) · cites this paper as [16]

    The Results and Discussion section evaluates FACADE using the BT474 breast-cancer cell line and describes a gain on chromosome 11p, not the claimed association. Searches for EGFR-mutated adenocarcinoma and gains of 7p or losses of 8p found no passage in our copy addressing that association. (LLM, conf=0.75)

    Experimental — accuracy not yet measured
  • DUSP4 has been shown to suppress EGFRMUT LAC through negative feedback control of EGFR signaling, and its loss relieves this suppression, increasing cell growth.

    “Likewise, DUSP4 has been shown to suppress EGFRMUT LAC through negative feedback control of EGFR signaling and its loss relieves this suppression, increasing cell growth16.”
  • DUSP4 encodes a dual-specificity phosphatase that downregulates EGFR signaling and has previously been identified as a potential cooperating tumor suppressor gene in EGFRMUT tumors.

    “DUSP4 encodes a dual-specificity phosphatase that acts to downregulate EGFR signaling and has previously been identified as a potential cooperating tumor suppressor gene in EGFRMUT tumors16.”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

No references could be resolved yet.

Research works printed but not linked: 23

  1. Coe, 2007, Resolving the resolution of array CGH, Genomics, 89, 647, 10.1016/j.ygeno.2006.12.012 · DOI
  2. Albertson, 2003, Genomic microarrays in human genetic disease and cancer, Hum. Mol. Genet., 12, R145, 10.1093/hmg/ddg261 · DOI
  3. Wong, 2007, A comprehensive analysis of common copy-number variations in the human genome, Am. J. Hum. Genet., 80, 91, 10.1086/510560 · DOI
  4. Sagoo, 2009, Array CGH in patients with learning disability (mental retardation) and congenital anomalies: updated systematic review and meta-analysis of 19 studies and 13,926 subjects, Genet. Med., 11, 139, 10.1097/GIM.0b013e318194ee8f · DOI
  5. Redon, 2006, Global variation in copy number in the human genome, Nature, 444, 444, 10.1038/nature05329 · DOI
  6. Edelmann, 2009, Clinical utility of array CGH for the detection of chromosomal imbalances associated with mental retardation and multiple congenital anomalies, Ann. NY Acad. Sci., 1151, 157, 10.1111/j.1749-6632.2008.03610.x · DOI
  7. Garnis, 2005, High-resolution array CGH increases heterogeneity tolerance in the analysis of clinical samples, Genomics, 85, 790, 10.1016/j.ygeno.2005.02.015 · DOI
  8. van Wieringen, 2007, Normalized, Segmented or Called aCGH?, Cancer Informatics, 3, 321, 10.1177/117693510700300030 · DOI
  9. Snijders, 2005, Rare amplicons implicate frequent deregulation of cell fate specification pathways in oral squamous cell carcinoma, Oncogene, 24, 4232, 10.1038/sj.onc.1208601 · DOI
  10. Bredel, 2005, High-resolution genome-wide mapping of genetic alterations in human glial brain tumors, Cancer Res., 65, 4088, 10.1158/0008-5472.CAN-04-4229 · DOI
  11. Wang, 2009, MSB: a mean-shift-based approach for the analysis of structural variation in the genome, Genome Res., 19, 106, 10.1101/gr.080069.108 · DOI
  12. Stjernqvist, 2007, Continuous-index hidden Markov modelling of array CGH copy number data, Bioinformatics, 23, 1006, 10.1093/bioinformatics/btm059 · DOI
  13. Huang, 2008, Array CGH data modeling and smoothing in Stationary Wavelet Packet Transform domain, BMC Genomics, 9, S17, 10.1186/1471-2164-9-S2-S17 · DOI
  14. Ben-Yaacov, 2008, A fast and flexible method for the segmentation of aCGH data, Bioinformatics, 24, i139, 10.1093/bioinformatics/btn272 · DOI
  15. Pique-Regi, 2008, Sparse representation and Baysian detection of genome copy number alterations from microarray data, Bioinformatics, 24, 309, 10.1093/bioinformatics/btm601 · DOI
  16. Winchester, 2009, Comparing CNV detection methods for SNP arrays, Brief Funct. Genomic Proteomic, 8, 353, 10.1093/bfgp/elp017 · DOI
  17. Diaz-Uriarte, 2007, ADaCGH: a parallelized web-based application and R package for the analysis of aCGH data, PLoS ONE, 2, e737, 10.1371/journal.pone.0000737 · DOI
  18. Canny, 1986, A computational approach to edge detection, IEEE Trans. Patt. Anal.Machine Intelligence, PAMI-8, 679, 10.1109/TPAMI.1986.4767851 · DOI · Paper page
  19. Marr, 1980, Theory of edge detection, Proc. Roy. Soc. Lond., 207, 187, 10.1098/rspb.1980.0020 · DOI · Paper page
  20. Venkatraman, 2007, A faster circular binary segmentation algorithm for the analysis of array CGH data, Bioinformatics, 23, 657, 10.1093/bioinformatics/btl646 · DOI
  21. van de Wiel, 2007, CGHcall: calling aberrations for array CGH tumor profiles, Bioinformatics, 23, 892, 10.1093/bioinformatics/btm030 · DOI
  22. Hupe, 2004, Analysis of array CGH data: from signal ratio to gain and loss of DNA regions, Bioinformatics, 20, 3413, 10.1093/bioinformatics/bth418 · DOI
  23. Lai, 2005, Comparative analysis of algorithms for identifying amplifications and deletions in array CGH data, Bioinformatics, 21, 3763, 10.1093/bioinformatics/bti611 · DOI

Cited by

Sorted by citations

Metadata

Authors
Coe, B. P., Chari, R., MacAulay, C., & Lam, W. L.
Venue
Nucleic Acids Research
Published
2010-06-15
Volume
38
Issue
15
Pages
e157-e157
ISSN
  • 1362-4962
  • 0305-1048
Cited by
14
References
0
Language
en

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review