Ting-You Wang

Data Beauty

PacBio Iso-Seq data analysis

December 08, 2020

An Introduction to PacBio Iso-Seq data analysis.

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Probabilistic Graphical Models for Fraud Detection

September 15, 2020

Probabilistic Graphical Models for Fraud Detection.

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An Introduction to Options

June 02, 2020

An Introduction to Options.

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Funding schemes for postdoctoral fellowship

February 05, 2018

A detailed list of funding schemes and opportunities for postdoctoral fellowships, curated/edited by Dieter Lukas, and eLife Ambassadors Juan Quintana and Aziz Khan.


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From Perceptron to Deep Learning

January 16, 2018

As a machine learning engineer, I have been learning and playing with deep learning for quite some time. Now, after finishing all Andrew NG newest deep learning courses in Coursera, I decided to put some of my understanding of this field into a blog post. I found writing things down is an efficient way in subduing a topic. In addition, I hope that this post might be useful to those who want to get started into Deep Learning.

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Introduction to Meta-analysis: fixed-effect model and random-effect model

September 08, 2017

What is a meta-analysis? As the name implies, a meta-analysis is an analysis of other people’s analyses o_O! when used correctly (in the context of a systematic review, for instance) meta-analysis is a powerful technique for understanding experimental effects. The great thing about meta-analysis is that it gets at the true effects that underlie probabilistic experiments (i.e., pretty much every experiment that isn’t physics). I think I have used the term “true” effect before, but all that I mean by that is the magnitude of the effect that we would be able to measure if we were able to collect data from an entire population. The gods might know what this effect is… but we mere mortals can only estimate it based on samples… and the better data we have, the more data we have, the better our estimates will be

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Recreate Economist graph by ggplot2

March 03, 2017

In this blog we would use some of those techniques to reproduce a graphic from the Economist ( Most of the part of this blog has been taken from the Harvard Labs class of Introduction to R Graphics )

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GWAS prephasing and imputation

February 20, 2017

Below shows a general workflow for carrying out a GWAS prephasing and imputation using 1000GP phase3. In this guide, I will focus on the processing of GWAS imputation in a detailed manner.

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RNA-seq data analysis (strand issues)

September 21, 2016

I had been working on strand-specific paired-end reads from HiSeq lately and I had trouble mapping reads back to assembled transcripts using STAR as well as using RSEM to estimate transcript abundance.

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RNA-seq data analysis

September 13, 2016

Below shows a general workflow for carrying out a RNA-Seq experiment. In this guide, I will focus on the pre-processing of NGS raw reads, mapping, quantification and identification of differentially expressed genes and transcripts.

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