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DNA Ghost:
This note based blog covers bioinformatics and cancer genomics
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A glance into tumor microenvironment
While reviewing a fascinating figure from Cell Science , Ghost came across an opportunity to discuss the tumor microenvironment (TME)—a...

Dimension reduction in RNA-Seq based model
While designing a model to describe a patient's immuno-oncology (IO) status, Ghost encountered a significant dimension reduction problem....


Propose a new way of tumor classification for immuno-oncology
First things first, the proposed classification are immune suppressing and immune escaping. Now let's go back for some specifics....

Developing cancer vaccine: Neoantigen identification and beyond
Immunotherapy has been the hot spot in cancer treatment in recent years. As a key component, neoantigen identification is usually done...

Depicting tumor clonal evolution
Tumor clonal evolution Cancer is stubborn largely due to its nature of heterogeneity: they evolve to adjust the changes of surrounding...


Calling somatic variants without matched normal
Identifying somatic mutation has always been challenging. Tumor heterogeneity The major challenge of calling somatic mutation is...

From variant calling approach: Frequentist vs Bayesian
Frequentist's approach: Assume sequencing error distribution. Frequentist's method makes the null hypothesis that non-reference allele is...

CNV detection II: Tumor CNV calling without matched normal
Ghost wrote a blog regarding tumor CNV calling with matched normal earlier. Here let's talk about what we can do when matched normal is...


Neural network: Escaping from non-global minimum traps
Deep learning has been the hot spot in recent years and shown excellent performance in many applications. In bioinformatics, Google has...

Matching cancer ontology with recurrent neural network
For people who have tried to build an oncology database or automated pipeline, one of the task is to define a standardized cancer type...
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