Few resources that I found extremely useful for statistical analysis / interpretation of biological data:

• Handbook of Biological Statistics: html This is a resource that will make help you to think through various steps in statistical analysis.
• For microarray analysis I would happily recommend "Microarrays For An Integrative Genomics" by Kohane, Kho and Butte. This is an amazing book on genomics (written in a easily accessible, text-book style format). This book explains various aspects of microarray analysis (biology, statistics, analysis, interpretation in great detail). It does not discuss any programming language, but provide pseudo-code to understand the concept, but you can easily adapt in your language of interest.
• This is an incredible lecture by Professor Warren Ewens on introduction of biostatistics from the perspective of genetics or genomics.

It is difficult to point to a single book that cover various statistical approaches in "high-throughput biology". IMHO, biological experiments are using every other statistical techniques out there. The statistical method that you should apply to your dataset will depend up on various aspects including your data and the question you want to answer. So, here I would like to point you to generic resource that you can use for better understanding of various statistical tests / models / methods.

• Statistics materials at Wolfram, Statistica, CMH website
• Statistics from machine learning / computer science perspective This will be useful if you are dealing with machine learning based approaches for the analysis of your biological data
• POLS Statistics is a very useful resource. For example here is a link with good description of all the major distribution that you will encounter in statistics.
• I would like to recommend a recent book that covers various generic statistical concepts from a mathematical perspective. See Data Analysis with Open Source Tools, a highly readable book that provides good understanding of various statistical methods like modeling, analysis, data mining with good description on the mathematical / statistical background of the concepts. The book also use open access tools like NumPy</a>, GnuPlot for the analysis and visualization of data.
• Think Stats: Probability and Statistics for Programmers PDF, which is a nice resource (also available from O'Reilly as a printed book)
• I also consult R / BioConductor package vignettes to understand the statistical background about the tests employed in individual packages

I just bought this one - "Intuitive Biostatistics". Really enjoyed the chapter on p-value ;)

This is the same problem I had faced a lot. The books and resources mentioned above are all excellent. Couple of resources that were very helpful to me other than mentioned above are:

1. Choosing and Using Statistics: A Biologist's Guide (link)
2. Statistics at the Bench: A Step-by-Step Handbook for Biologists (link)
3. Statistics for Terrified Biologists(link)

Apart from these book, some of the articles that were very helpful to me recently:

1. P-values, False Discovery Rate (FDR) and q-values(link)
2. Principal component analysis:
   • What is principal component analysis?(link)
   • Principal component analysis of genetic data(link)
3. Collection of Biostatistics Research Archive(link)
4. Guide to Biostatistics(link)

One very nice place to learn general concepts about statistics which can be applied in this field: Khan Academy Statistics videos (link)

Hope this is helpful.

I think "Statistics: an introduction using R" is a good book. Short and to point on the theory and application of the common basic statistical methods. The R examples could also be useful if you're currently using this language.

I have recently published an ebook on Biostatistics.

Biostatistics – When Pain becomes Treatment- http://amzn.to/2gh2M1F

Hopefully, it will be of help to you...

I've heard only positive about this one from Susan Holmes and Wolfgang Huber:

https://www.huber.embl.de/msmb/