http://www.ncbi.nlm.nih.gov/pubmed/23307812

http://bioen-compbio.bioen.illinois.edu/RACA/

Address of the bookmark: http://bioen-compbio.bioen.illinois.edu/RACA/

java -jar trimmomatic-0.35.jar PE -phred33 input_forward.fq.gz input_reverse.fq.gz output_forward_paired.fq.gz output_forward_unpaired.fq.gz output_reverse_paired.fq.gz output_reverse_unpaired.fq.gz ILLUMINACLIP:TruSeq3-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36

This will perform the following:

• Remove adapters (ILLUMINACLIP:TruSeq3-PE.fa:2:30:10)
• Remove leading low quality or N bases (below quality 3) (LEADING:3)
• Remove trailing low quality or N bases (below quality 3) (TRAILING:3)
• Scan the read with a 4-base wide sliding window, cutting when the average quality per base drops below 15 (SLIDINGWINDOW:4:15)
• Drop reads below the 36 bases long (MINLEN:36)

More at http://www.usadellab.org/cms/?page=trimmomatic

Address of the bookmark: http://www.usadellab.org/cms/?page=trimmomatic

Natural selection and other evolutionary forces lead to particular patterns of evolutionary dynamics, and they leave characteristic signatures on the genetic variation within populations. We use a combination of theory and experiments to study the dynamics and population genetics of natural selection in asexual populations such as microbes and viruses.

We use both theory and experiments to study evolutionary dynamics and population genetics, particularly in situations where natural selection is pervasive.

http://desailab.oeb.harvard.edu/home

1. Setting up your computing environment
2. Retrieving and storing sequencing files (your own data or from public sources)
3. Checking sequence quality, trimming, general sequence manipulation
4. Mapping reads to a reference genome
5. Manipulating SAM/BAM alignment files
6. Visualizing data in a genome browser

RNA-Seq

1. De novo transcript discovery and differential analysis with Cufflinks
2. Differential expression analysis with R/Bioconductor
3. Clustering of large expression datasets (microarray or RNA-Seq)

Microarray

1. Basic analysis of Affymetrix Gene Expression Arrays using R/Bioconductor

General Tips for Data Analysis

1. Excel workarounds, adding gene annotation, X-Y plots tips, etc.

Address of the bookmark: http://homer.salk.edu/homer/basicTutorial/

Address of the bookmark: http://bioinformatics.ua.pt/software/smash/

More at https://gatb.inria.fr/

Address of the bookmark: https://gatb.inria.fr/

This page is a HOWTO guide for setting up a SLURM installation, currently focused on a CentOS 7 Linux OS. Please send feedback to Ole.H.Nielsen /at/ fysik.dtu.dk.

See the SLURM homepage (also https://computing.llnl.gov/linux/slurm/).

Address of the bookmark: https://wiki.fysik.dtu.dk/niflheim/SLURM

Monsanto is seeking a very talented Genomics Scientistto become an integral member of our Global Pipeline Analytics team with a focus on quantitative genetics. The ideal candidate will have familiarity with modeling and analysis of genetic data sets using a variety of statistical techniques.

Major Responsibilities:
- Provide guidance on experimental design for genomic-related experiments
- Familiarity with analysis of the following methods: GWS, QTL, eQTL, RNA-Seq
- Provide written and oral presentations of methods, results, conclusions, and recommendations to peer and management groups.
- Ensure timely delivery and clear communication of results
- Develop strong and successful collaborations among various Monsanto enabling teams.

Required Skills:

- PhD degree in Statistics, Biostatistics, Statistical Genetics, Quantitative Genetics, Breeding, Bioinformatics or a related field with 2 years of experience
- Working knowledge and experience with one of the following quantitative languages:R, Python, Perl, SAS
- Background in Windows and Linux operating systems
- Very strong problem solving skills will be required to work well as a member of a dynamic team
- Strong verbal and written communication skills.
- Demonstrated ability to deliver timely results and be results oriented.
- Extensive knowledge of quantitative genetics and experimental design. 
- Demonstrated track record of solving challenging and complex problems.

Desired Skills/Experience:

- Excellent communication skills, with the ability to summarize complex concepts in language understandable by scientists from a variety of disciplines.
- Experience in agronomy and/or plant breeding in vegetables or row crops.

Please apply to
https://jobs.monsanto.com/job/st-louis/genomics-scientist/769/2081771

This readme covers all necessary instructions for the impatient to get andi up and running. For extensive instructions please consult the manual.

More at https://github.com/evolbioinf/andi/

Address of the bookmark: http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full