Some interesting poster which is useful for our scientific career and basic skills:
Writing reviews of academic papers: https://github.com/jtleek/reviews
A guide to reading scientific papers: https://github.com/jtleek/readingpapers
Good Habit for Bioinformatics Analyst: Good Habit for Bioinformatics Analyst or Scientist
Lab notebook for data analysis work: recommendation on lab notebook for bioinformatics/data analysis work
Most Common Stupid Mistakes: What Are The Most Common Stupid Mistakes In Bioinformatics?
9 Common metrics to measure tissue specificity: http://www.ncbi.nlm.nih.gov/pubmed/26891983
Bayesian tool for methylation analysis: https://en.wikipedia.org/wiki/Bayesian_tool_for_methylation_analysis
Cluster analysis to methylation data: http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-9-365
How to share your data as public hub at UCSC: http://genomewiki.ucsc.edu/index.php/Public_Hub_Guidelines
List of open-source bioinformatics software: https://en.wikipedia.org/wiki/List_of_open-source_bioinformatics_software
Software you need to prepare better figure: Illustrator, Photoshop, Cytoscape, Mega, heatmap.2, String 9.0, Venn, smoothScatter
Performance of 30 different pipelines to make variation and Indel callling: http://www.hindawi.com/journals/bmri/2015/456479/
Windows user? Strawberry Perl is better than active perl in the usage of bioperl (lastest active perl not support bioperl).
Install BioPerl Without Root Privilege in Linux: How To Install BioPerl Without Root Privileges in Ubuntu/Linxu
Deconvolution Methods on RNA-Seq Data: Deconvolution Methods on RNA-Seq Data (Mixed cell types)
PCR primer batch design: http://batchprimer3.bioinformatics.ucdavis.edu/cgi-bin/batchprimer3/batchprimer3.cgi
Use Ensembl annotation, rather than UCSC or other annotation and be sure to note the version of Ensembl annotation
Circular RNAs (circRNAs) database: http://circnet.mbc.nctu.edu.tw/
Pathway, GO and Enrichment Analysis: Enrichr : http://amp.pharm.mssm.edu/Enrichr/
How to get MSI (Microsatellite Instabilty) status in TCGA Project: TCGA MSI status
A program for reliable multiplex PCR primer design: http://biocompute.bmi.ac.cn/MPprimer/
Prepare all the script in github (Version Control System) and prepare the Rmd for records.
Multiple data cluster (mRNA, Methylation, CNV, Mutation): iCluster
Mutation calling: MutSig
BBSplit: Read Binning Tool for Metagenomes and Contaminated Libraries
categorical different domain tools - - http://molbiol-tools.ca/
Its time to add: The Biostar Handbook: A Beginner's Guide to Bioinformatics
How about:
The Art of Unix Programming: http://www.catb.org/esr/writings/taoup/html/
Grymoire: http://www.grymoire.com/
Software you need to prepare better figure:
Why not GIMP and Inkscape ? These are very useful free softwares for Linux users (Inkscape is available for Windows users too,FREE). And in R 'pheatmap' and 'ggplot2'.
It is not free but I have used Adobe Acrobat Pro to great effect. If your institution has access to it, check it out as well. Very useful to touching up the text on PDF figures.
Inkscape is an awesome free-source alternative to Adobe Illustrator whereas GIMP is a free-source alternative to Adobe Photoshop. Both are good tools depending on what your ultimate aim is. GIMP/Photoshop are raster/bitmap graphics and are often used to edit photographs by adding effects and making them stylish. Inkscape/Illustrator, on the other hand, are vector-based graphic editor software which are used for more precise and mathematical graphics designing. Vector-based files allow you to size your figures properly without losing resolution, as they can be altered in size while maintaining high print-quality resolution which is what you're going to need if your submitting for publication in Science, Nature, PNAS etc.
ggplot2 is awesome! Here's two links I would strongly suggest checking out 1) Getting started with ggplot2 2) Top 50 ggplots (with code)
I agree pheatmap is a nice package (the "p" stands for pretty-heatmap) and it's intuitive to use; however, sometimes you may want/need to arrange multiple heatmaps or add multiple layers of annotation so I would suggest learning ComplexHeatmap. If you're doing EDA, sharing heatmaps with collaborators, or something special for the supplements, try out Interactive Heat Maps for R Using plotly>.
I like this Shiny App for Venn Diagrams.
It is a nice paper for whole exome pipelines comparison:
Systematic comparison of variant calling pipelines using gold standard personal exome variants
http://www.nature.com/articles/srep17875