Daily

Make it simple

13/6

[ ] Julia Wrapper for MINE

11/6

[ ] website ltguo.me
[ ] c++
[ ] DSA

14/9

[ ] first step with Julia

10/9

[ ] first step with Julia

8/9

[x] reinstall ubuntu
[x] return key and card
[x] build julia, tensorflow, hexo
[ ] first step with julia

7/9

[x] resign signments etc.
[x] shopping for basic life
[x] Jeff Dean's presentation on Deep Learning Summer School
[x] A tour through the tensorflow codebase

6/9

[x] move home
[ ] build julia, openssl, libgit2, curl etc

5/9

[ ] build julia, openssl, libgit2, curl etc
[x] learn from the 10th old competitor
[ ] setup octopress blog system

4/9

[x] emacs various mode
[ ] serizure prediction data preprocessing

1/9

[ ] shared memory in different process
[x] write notes about lecuter 13,14 of cs231n

31/8

[x] write notes about lecture 8~13 of cs231n

30/8

[x] write notes about lecture 1~7 of cs231n

29/8

[x] Finish writing for company
[ ] cs231n, cs224d slides
[ ] tensorflow usage
[ ] write a blog about bazel build in tensorflow

28/8

[x] add about in my blog
[x] basic c call cpp, julia call c demo
[x] Deep Reinforcement Learning one of Four without lab1

27/8

[ ] MINE.jl
[x] learn emacs
[ ] blog about emacs, gdb and c++

26/8

[x] get faimilar with tensorflow
[x] try to preprocess data with tensorflow

25/8

[x] learn the preprocessinng API of tensorflow
[ ] build LSTM_CNN model

24/8

[x] the bug of pywrap_tensorflow disappeared and everything goes toward expected.
[x] learn various tutorials and sovle a segment fault (core dumped) due to out of memory
[ ] learn how to build sophisticated RNNs and CNNs

23/8

[x] learn to work with tensorflow source code
[x] the layout of tensorflow source code
[x] swig
[x] understanding and visualizing CNN
[x] finished files for the development of NGS data analysis core software

21/8

[x] learn to how to build RNNs with TensorFlow

20/8

[ ] fist step with Julia
[ ] build simple LSTM to predict chr1 with torch

19/8

[ ] build DBLSTM to predict sequence on chr1

18/8

[x] apply torch-rnn to Genome
[x] build Deep Bidirectional LSTMs with rnn in torch7

17/8

[x] LSTMs with torch
[x] prepare blog of dllab.org
[x] test post with octopress

16/8

[ ] train CNN, LSTMs with Torch

9/8

[ ] faimilar with LSTMs
[ ] Genome data

8/8

[x] check the correctness of data and train benchmark model

7/8

[x] quick go through CS224d from 15:30 to 18:00

27/7

Refactor code of DeepSomaticSNV

[x] data preprocessing
[ ] model various parameters
[ ] various stats such as log analysis

20/7

[ ] train sgRNA dataset

19/7

[x] two+ paper of sgRNA
[x] download ImageNet datasets

18/7

[x] train LeNet-5 CNN
[ ] test ResNet on toy dataset

Beat MSR

[ ] STARS

Gideon

Mini Julia
Julia for CUDA
CodeAnalysis.jl for Julia, C, C++
Kaleidoscope.jl
COOL, COOL.jl
new topology and opt algorithm for network

15/7

[ ] baseline of Project S
[ ] dig 14 paper

14/7

[x] data preprocess
[ ] CNN/softmax as base model
[x] read 14 Broad's paper

13/7

[x] deep learning on genomics

11-12/7

[ ] 14Broad's paper

8/7

[ ] download all the genomes from ensembl

7/7

[ ] vyper pipeline
[ ] fix bug of keyerror

5/7

[x] MSR's code: not clear the way of hack
[x] GeneticAlgorithm called
[x] mechanisms of sv: look througth a little
[x] vyper pipeline and get breakpoint, not done

4/7

[x] weekly summary and plan
[ ] DataExpore.jl
[ ] MH question
[ ] STRs and homopolymers
[ ] sgRNA design basics

3/7

[x] GRE word 2 day
[x] JuliaCon machine code

2/7

[x] Julia.h julia_internal.h
[x] JuliaCon2016 part videos
[x] GRE 2 days words

1/7

[ ] MH Vy-PER paper comprehension
[ ] dive to Azimuth code and algorithm
[ ] read paper of Azimuth
[ ] try to learn some NoSQL databases

29/6 - 30/6

[x] collect data relevant to Proj S, the result is collect several labs
[x] understand 2016 but still a lot of questions

28/6

[x] read MR's paper again
[x] funetine pipeline of Vy-PER

27/6

summary of last week
plan of this week
communicate with Hu
reading paper from MR one time

25/6

[x] run vyper
[x] run azimuth

24/6

[ ] finish vy-per testing
[ ] reading all the code of azimuth

22/6

[ ] rewrite final_fitering

19/6

[x] rewrite blatsam and test it on real data

18/6

[x] test julia version of Vy-PER and rewrite sam2fas

17/6

[x] test julia version of Vy-PER

16/6

[x] digest Vy-PER

15/6

[x] pass Vy-PER on next-generate sequence data without the final filter

14/6

[x] run Vy-PER on my data

13/6

[x] Vy-PER

10/6

[ ] COOL

Julia TODO

[ ] WARNING: could not import Base.complement into DataStructures WARNING: could not import Base.complement! into DataStructures
[x] IO regression and readavailable(IOStream)
[x] fucntion sequence()::Int64 end not clear error msg

[ ] methods of fieldname and fieldnames are not consistent


julia> type Test
          a::Int64
          b::String
        end
        t = Test(1,"hello")
Test(1,"hello")

julia> fieldnames(Test)
    2-element Array{Symbol,1}:
:a
:b

julia> fieldnames(t)
 2-element Array{Symbol,1}:
  :a
  :b

julia> fieldname(Test,1)
  :a

julia> fieldname(Test,2)
  :b

julia> fieldname(t,1)
  ERROR: MethodError: no method matching fieldname(::Test, ::Int64)
  Closest candidates are:
    fieldname{T<:Tuple}(::Type{T<:Tuple}, ::Integer)
      fieldname(::DataType, ::Integer)
       in eval(::Module, ::Any) at ./boot.jl:225
        in macro expansion at ./REPL.jl:92 [inlined]
         in (::Base.REPL.##1#2{Base.REPL.REPLBackend})() at ./event.jl:46


- getfield exits but not getfields
- string concation * ^
- print_with_color is too long to write and use

### 2/6
- MH done

### 1/6
- HIVID make it done

### 31/5
- Bug: Pkg.update false
- Julia: julia.h, julia_internal.h
- **HIVID: aln, overlap, merge, aln, location**

### 30/5
- Finish Overlap.jl
- A sold understanding about julia.h

### 11/5
- make a reference contains hg19 and all hpvs
- HPVID base version

### 10/5
- HPVID base version [not finished]

### 9/5
- HPV integration

### 6/5
- MITx Unit3,4
- Fix BHTsne.jl 
- Fix MINE.jl
- Familar with LLVM IR and Assembly

### 5/5
- LLVM 
- Julia Deeper
- Assembly
- CPP

### 4/5
- LLVM
- ccall

### 30/4
- `StrPack.jl` to replace `struck` module in Python

### 28/4
- [ ] APIs of htslib

### 27/4
- [ ] htslib.jl bam APIs finished

### 16/4
- [ ] tensorflow

### 15/4
- [ ] learn how to use tensorflow 

### 14/4
- [ ] pyjulia and cnn, lstm in tensorflow

### 13/4
- [ ] aliyu

### 12/4
- [ ] tensorflow, docker and aliyun

### 11/4
- [ ] cnn Mocha

### 10/4
- [ ] deep learning getting

### 9/4
- [ ] learn cnn 

### 8/4
- [ ] make bam2pileup matrix to hdf5 file

### 7/4
- [ ] DarkVC

### 4/4
- [ ] papers about deep learning bio 

### 2/4
- [x] DeepSEA releated

### 1/4
- [x] PPT
- [x] compare prefermance of M2 and Varscan2

## month 3 / 2015

### 30/3
- [ ] machine learning applications on Gene
- [ ] compile gatk-engine
- [ ] deep learning on gene expression and predict varant effects

### 29/3
- [x] DeepSEA
- [x] learn Lua

### 28/3
- [x] fix erros while building miniutils with bazel 

### Month Goal
- [ ] GATK

### Week Goals
- [ ] Be able to use classes in GATK 
- [ ] finish local assembly with De Bruijn Graph 1
- [ ] finish PairHMM 2-3
- [ ] finish FM-index aligner 4

### 27/3
- [ ] minigatk with bazel

### 26/3
- [ ] master Bazel

### 25/3
- [ ] minimum gatk with Bazel 

### 24/3
- [ ] write a new walker based on Mutect2 with GATK in java and scala

### 23/3
- [ ] write a new walker based on Mutect2 with GATK in java and scala

### 22/3
- [x] Fully understand intelij idea => part
- [x] java unit test for GATK  => GATK its own test
- [x] how to write a new walker with GATK in java and scala => part

### 21/3
- [ ] De Bruijn Graph
- [ ] Test Mutect2 local assembly part with data
- [ ] how to use GATK in a new package both in java and scala
- [x] Tests in GATK

### Week Goals
- [x] hack M2 throught
- [x] Parallel MuTect2 on Cluster

### 20/3
- [x] DSA TsingHuaX week 1 and rank 107

### 19/3
- [x] nfs for x03 haplox success
- [ ] De Bruijn Graph for local assembly julia package
- [ ] PairHMM for pair alignment julia package
- [x] spark standalone cluster success

### 18/3
- [x] Presentation about M2
- [x] make PPT
- [ ] pick algorithm

### 17/3
- [x] deep understanding of M2 

### 16/3
- [x] parallel M2 on queue
- [x] deep understanding of M2 

### 15/3
- [x] M2 Math part TODO

### 14/3
- [x] M2 code part

### Week Goals
- [ ] Parallel pipeline with Queue
- [ ] hack M2 throught
- [x] learn scala and java

### 13/3
- [x] learn spark

### 12/3
- [x] learn java by Edx course
- [ ] learn scala by Courera course

### 11/3
- [ ] backgroud nosie mode
- [ ] pipeline parallel only GATK part
- [ ] MuTect2 Rewrite with scala with 3 days

### 10/3
- [x] parallel MuTect2

### 9/3
- [ ] transfer pipeline to cluster
- [ ] go throught ScalabyExample
- [x] scala cheatsheet and simple examples 

### 8/3
- [x] find feature for 6+9 samples of lung cancer and normal => gene mutations
- [x] prepare clustering code

### 7/3
- [x] hack Mutect2 
- [x] find feature for 6+9 samples of lung cancer and normal

### 3/3
- [x] learn scala by 10miniutes
- [x] learn java  by 10minimutes
- [x] hack Mutect2
- [x] hack capp stanford
- [x] write week report

### 2/3
- [x] read papers and write varant callers review  50%

### 1/3
- [ ] Finish pipeline: finished 60%
- [x] beta-bionomial distribution

## month 2 / 2015

### 29/02
- [x] mpileup APIs of htslib 
- [ ] CS231 assignment 1 50%
- [x] download and browse most of variant call papers during 2012-2016
- [x] finish most of code about pipeline and wait to bug
- [x] Ng's ML about mixture of Gaussians

### 28/02
- [x] Game Theory Week Two
- [x] CS231n segmentation video

### 27/02
- Game Theory

### 26/02
- samples pileup stats
- Data scitentis toolbox at Coursera

### 25/02
- eval the feature of err baseline

### 24/02
- Simulate data with BAMSurgeon
- Variant Call with various callers

### 23/02
- Get underlining principle of BAMSurgeon 

### 22/02
- VariantCall for ctDNA: check varscan2

### 20/02
- Fun.jl

### 19/02
- **osx support**

### 18/02
- stat tec support for production manager finished
- **illumina barcode demutiplex** finished
- osx support

### 17/02
- htsFile
- production related
- illumina barcode demutiplex
- tensorflow udacity assignments

### 16/02
- htslib 
- 931 genes related

### 15/02
- htsFile

### 14/02
- htslib query

### 12/02
- fix htslib's bug

### 08/02
- fix bam query bug

## month 1 / 2015

### 1/30
- prepare notebook etc for home

### 1/29
- bam/sam hdr write 
- bam index

### 1/28
- bam write and bam header IO

### 1/27
- hight level wrapper of bam read, write and query

### 1/26
- bam read and bam write

### 1/25
- bam read formal form
- paper about tumor evolution
- DL of Google

### 1/24
- L1,L2,L3 of DL course from Google

### 1/23
- Deep Learning from Google

### 1/22
- make read bam true

### 1/21
- SeqErrorDetector draft

### 1/20
- HTSLIB.jl

### 1/19
- looking for extreme sparse models in ICML NIPS ICCV and other top journals

### 1/18
- vcf data mining

### 1/17
- assign 1
- week summary

### 1/16
- lecture 3

### 1/15
- check models

### 1/14
- hand compare mutations between Small intestine and Biliary tract

### 1/13
- predict

### 1/12
- model vcf part finish

### 1/11
- fix codes about work
- lecture 2 of cs341n
- check basset

### 1/10
- a good materal: cs341n:Convolutional Neural Networks for Visual Recognition

### 1/9
- Finish work not done of this week
- Apply Deep Learning to kaggle tasks

### 1/8
- report
- MXNet.jl
- apply MXNet.jl

### 1/7 
- rewrite Fusion dectect codes
- use all the haplox data

### 1/6
    find the methods of handle false positive

### 1/5
    finish the model part 

### 1/4
    finish Strict except a good model

### 1/3
    hackerrank python
### 1/2
    9:30-11:00 readdoc,julia
    11:30-2:00 hackerrank python
    2:00-5:30 apply tensorflow to  one kaggle dataset
    5:00-7:00 spark,scala
    8:00-22:00 lan,network,htslib
    readdoc and intro to network, hackerrank, julia, lan
    one or two machine learning or deep learning package 
    spark, scala
### 1/1
    learn Readdoc and hackrank
    learn introduction to network of stanford
## month 12 / 2015
### 12/31
    just remains a few bugs of work. Go to Deep for now.

### 12/30
    focues the classification task.

### 12/29
    make GeneMisc ready for users and prepared to regeister

### PLAN of This Week
    test my model in real cfDNA data

### 12/25
    finish and test gene_location and gene synonym

### 12/24
    Summary about my skills:
        One, mathematics including machine learning, mathematical optimization, PGM.
        Two, computer science including DSA, GPU computing, compiler.

### 12/3
    Flash extended and Alogorithms_stanford urgent

### 12/2
    finish Flash Project

## month 11 / 2015

### 11/27 
    too much ideas to execute so that achived nothing
    First, classification with an emphase on feature selection
    Second, GP tune hyperpara
    Third, PGM / DBM

### 11/4
    1. Learn the structure of COSMIC by PGM
    2. feature selection with random search
### 11/3
    A great idea come in mind.
    chose hyperparameter and do feature selection with Guassian Process

## month 10 / 2015

### 10/27

    summary current published work on cancer risk prediction

Plan daily since 10/26/2015

zhmz90 / Daily

readme

Daily

Make it simple

13/6

11/6

14/9

10/9

8/9

7/9

6/9

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4/9

1/9

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9/8

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27/7

20/7

19/7

18/7

Beat MSR

Gideon

15/7

14/7

13/7

11-12/7

8/7

7/7

5/7

4/7

3/7

2/7

1/7

29/6 - 30/6

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10/6

Julia TODO