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Feb 19, 2016
Category: Academic
Posted by: sro
Hari pertama pada pekan kolokium S1 Departemen Statistika, selamat berkolokium !!!
Feb 14, 2016
Category: Academic
Posted by: sro
Berikut ini daftar hasil rekruitmen asisten mata kuliah S1, semester genap tahun ajaran 2015/2016, Departemen Statistika IPB
Feb 9, 2016
Category: Academic
Posted by: sro

Pendaftaran Asisten S1 pada Semester Genap telah dibuka, segera mendaftar!!!

Pendaftaran pada link:

http://goo.gl/I9u4jG

 

Biostatistics Workshop

Next Generation Sequencing Data Analysis: A Practical Introduction

 

October 21st, 2017

IPB International Convention Center (IICC), Bogor

Register on: s.id/biostatistics

 

Payment information

To join this workshop, the candidate participants have to pay the workshop fee by transfer via bank:

Bank Mandiri
Acc name: Dept. Statistika FMIPA IPB
Acc number: 133 – 00 – 1143069 – 1
 
with fee criterias IDR 800.000/person NETT.
 
The proof of transfer payment have to be sent by email to both rahardiantoro.stk@gmail.com and r.rahma.anisa@gmail.com
 
 
 
 
 

Software Preparation & Materials

 

These are the software that need to be installed in the server (please ensure that the paths to the executable files are added to bash.profile file):

- FastQC
- FastX toolkit
- Trimmomatic
- Samtools
- Bowtie2 (if it has not been installed)

Please also install the Bioconductor suite from inside R using this command:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite()

After installing the suite, you will need to install the following packages:
biocLite("tweeDEseqCountData")
biocLite("edgeR")
biocLite("RSamtools")
biocLite("qvalue")
install_github("genomicsclass/tissuesGeneExpression")
install_github("genomicsclass/GSE5859Subset")
install.packages("rafalib")
install.packages("irlba")
install.packages("mclust")
install.packages("RColorBrewer")
biocLite("MAST")
biocLite("scde")


Materials

Lecture 1: Brief introduction to next-gen sequencing (NGS), Statistical Methods for NGS Data
Lab 1: Practical NGS Data Analysis
From Quality Control (QC) to DE analysis
Lecture 2: Brief introduction to single-cell omics technology, Statistical Methods for Single-Cell Omics Data
Lab 2: Practical single-cell Data Analysis
Quality controls, clustering, pseudo-time and DE analysis

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