48 Matching Annotations
  1. Oct 2017
  2. May 2017
    1. Precision: It is a measure of correctness achieved in positive prediction i.e. of observations labeled as positive, how many are actually labeled positive. Precision = TP / (TP + FP) Recall: It is a measure of actual observations which are labeled (predicted) correctly i.e. how many observations of positive class are labeled correctly. It is also known as ‘Sensitivity’. Recall = TP / (TP + FN)

      Example: In cancer research you may want higher recall, Since you want all actual positive observations to classified as True Positive. A lower Precision maybe alright because some healthy people classified as cancerous can be rectified later.

  3. Apr 2017
    1. The Administration could also exercise its regulatory authority—most potently, to direct the Centers for Medicare and Medicaid Services (CMS) to allow reimbursement for molecular profiling of cancers

      Perhaps the most important measure to keep precision medicine initiate alive. Surge in risk and treatment response prediction in genomic assays is of little value without practical means of affordable molecular profiling of a patient's tumor or more importantly, pre-diagnosis genomic screen.

  4. Aug 2016
    1. a different and relatively unclear pattern

      different and inconsistent patterns

    2. Presumed


    3. really low

      no or low (<10%)

    4. Thedata displayedthat it is roughly possible to

      My data suggest that it is possible to qualitatively

    5. a totally reliable method

      considered quantitative

    6. used for measurements ofheart

      primer sets are not tissue-specific; you used them for all tissues; only the measurements themselves are tissue-specific

    7. the expression of transcripts


    8. qRT-PCR

      qRT-PCR cannot show transcription termination: all it can do is verify the RNAseq data, i.e., more relatively more transcription upstream of an active CGI compared to transcription across the CGI. It is important to be precise about what qRT-PCR can and cannot do.

    9. transcripts terminating


    10. transcripts terminateacross

      transcription extends across

    11. transcripts terminating


    12. different samples


    13. more

      orders of magnitude more

    14. sodium-bisulfite

      sodium metabisulfite

    15. data

      depth-of-sequencing-normalised and log-transformed read coverage data

    16. RNA-seq data


    17. activity

      transcriptional activity

    18. which means that onlythe intragenicpromoter influencestissue-specific gene transcription

      reducing the potential of tissue-specific host promoter activity confounding the observations

    19. RNA-seq data


    20. RNA-seq data


    21. (blue box)

      (low blue data point)

    22. upstream

      terminating upstream

    23. (red diamond)

      (high red data point)

    24. (lower left cornerof the figure)

      (low x value)

    25. (red diamond in the bottom right cornerindicate transcripts across)

      (large difference in y values: high blue versus low red data point)

    26. (upper right cornerof the figure)

      (large x value)

    27. transcripts

      amount of fragments spanning

    28. transcripts terminating

      (scaled) amount of cDNA fragments mapping

    29. RNA-seq data


    30. from a large difference to a non-existing difference in absoluteterms

      no difference between across and upstream

    31. terminating across than upstream

      extending across than terminating upstream

    32. RNA-seq data plots were

      A scatter plot of intragenic CGI activity versus the upstream and across quantities for all 30 tissues was

    33. scalingfora comparable dataset

      scaling across tissues to make quantities comparable

    34. conducting a permutation test for resampling of the dataset

      randomly permuting the intragenic CGI activities across tissues

    35. fragment

      aligned sequenced cDNA fragments

    36. overlapping with the host gene

      spanning across the intragenic CGI

    37. exonic

      host gene exon-anchored

    38. sense and antisense orientation

      separately for the sense and antisense orientations of transcription from the CGI relative to the host gene

    39. CGIs

      CGI transcriptional states

    40. Dnmt1 copies

      during cell division

    41. DNA methylation

      in vertebrates (in bacteria, 5mA is common)

    42. there may be different methylation patterns

      too vague

    43. it

      what is 'it'?

    44. -most exon


    45. heritable

      mitotically or meiotically heritable