Why Normalize RNA-Seq Data?

Normalization is a crucial step in RNA-Seq analysis for the following reasons:

• Sequencing depth: Different RNA-Seq experiments produce varying numbers of reads, making direct comparisons between samples misleading.

• Gene length: Longer genes inherently generate more reads, irrespective of their actual expression level.

• Bias reduction: Normalization mitigates technical biases, enabling meaningful biological interpretation.

TPM (Transcripts Per Million)

TPM measures the proportion of reads mapped to a transcript, normalized by transcript length and sequencing depth. It is calculated as:

Key Features:

1. Proportionality: TPM values sum to 1,000,000 across all transcripts in a sample, making it easier to compare between samples.

2. Intuitive interpretation: TPM values directly represent the abundance of transcripts in a sample.

3. Preferred for comparisons: TPM facilitates between-sample comparisons better than FPKM.

FPKM (Fragments Per Kilobase Million)

FPKM normalizes read counts by transcript length and sequencing depth, but without enforcing proportionality like TPM. It is defined as:

Key Features:

1. Historical significance: FPKM was one of the first normalization methods used for RNA-Seq.

2. Single-end vs. paired-end: In paired-end sequencing, FPKM becomes RPKM (Reads Per Kilobase Million).

3. Limited utility: FPKM values are not as robust as TPM for cross-sample comparisons due to lack of proportionality.

CPM (Counts Per Million)

CPM normalizes raw read counts by sequencing depth, without considering gene length. It is expressed as:

Key Features:

1. Simplicity: CPM is straightforward and computationally less intensive.

2. Application: Suitable for non-length-dependent analyses, such as comparing total expression levels or differential expression analysis.

3. Gene length agnostic: CPM does not correct for gene length, making it less ideal for measuring expression levels.

When to Use Each Method

• TPM: Best for comparing expression levels between samples, especially when transcript length and sequencing depth vary.

• FPKM: Useful for historical consistency but generally replaced by TPM.

• CPM: Ideal for differential expression analysis when gene length normalization is unnecessary.

Conclusion

Choosing the right normalization method depends on the specific objectives of your RNA-Seq analysis. TPM’s proportionality and robustness make it the preferred choice for most applications, while CPM serves well for differential expression studies. Although FPKM paved the way for RNA-Seq normalization, it has largely been supplanted by TPM in modern workflows. Understanding these methods and their nuances ensures accurate and meaningful interpretations of RNA-Seq data.

References:

1. Li, B., & Dewey, C. N. (2011). RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics.

2. Trapnell, C., et al. (2010). Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nature Biotechnology.

3. Law, C. W., et al. (2014). voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biology.

Who you are
You’re someone who wants to influence your own development. You’re looking for a company where you have the opportunity to pursue your interests across functions and geographies. Where a job title is not considered the final definition of who you are, but the starting point.

Qualifications:
Major: Bioinformatcis or biology major who is interested and wants to learn Biocomputing, At least 2 years of college.
Basic knowledge of LINUX and programming, e.g., perl, python, XML.

More at http://www.roche.com/careers/jobs/jobsearch/job.htm?id=E-00437679&locale=en&title=Summer%20Intern%20-%20Research%20Bioinformatics

Online version and downloadable software package for offline use (source code in PERL) freely available at http://bat.ina.certh.gr/tools/circoletto/

Contact:ndarz@certh.gr

Address of the bookmark: http://tools.bat.infspire.org/circoletto/

Name of the Scheme : Distributed Information Sub Centre – DISC

Qualifications : M.Sc/ B Tech in Bioinformatics with NET/GATE or M Tech in Bioinformatics

Number of posts : One

Emoluments : Rs. 25,000/-

Upper age limit : 35 years for Men & 40 years for Women as on date of Interview
How to apply

Date of Interview : 12-03-2015 at 10.00 AM. All relevant certificates (in original) and bio data, No objection certificate in case he/she is employed elsewhere and experience certificate in original (if any) need to be produced at the time of interview.

More at http://spices.res.in/index.php?option=com_content&view=article&id=263

Ability to detect, quantify, and visualize complex and de-novo splicing variations from RNASeq.

MAJIQ’s accuracy compares favorably to other algorithms.

MAJIQ 2 is *way* faster, more memory and I/O efficient

New visualization (VOILA 2.0) Ability to analyze hundreds and thousands of samples Why so negative? (Support for a confident negative set)

Finally, a major reason we are excited about MAJIQ 2.0 is that it sets the code base for many new exciting algorithmic and visualization improvements, with application to new research questions so stay tuned!

More at https://biociphers.wordpress.com/2019/04/01/majiq-2-is-out/

Address of the bookmark: https://majiq.biociphers.org/

This is a short post giving steps on how to actually install R packages. Let’s suppose you want to install the ggplot2 package. Well nothing could be easier. We just fire up an R shell and type:

> install.packages("ggplot2")

In theory the package should just install, however:

• if you are using Linux and don’t have root access, this command won’t work.
• you will be asked to select your local mirror, i.e. which server should you use to download the package.

Installing packages without root access

First, you need to designate a directory where you will store the downloaded packages. On my machine, I use the directory /data/Rpackages/ After creating a package directory, to install a package we use the command:

> install.packages("ggplot2", lib="/data/Rpackages/")
> library(ggplot2, lib.loc="/data/Rpackages/")


It’s a bit of a pain having to type /data/Rpackages/ all the time. To avoid this burden,  we create a file .Renviron in our home area, and add the line R_LIBS=/data/Rpackages/ to it. This means that whenever you start R, the directory /data/Rpackages/ is added to the list of places to look for R packages and so:

> install.packages("ggplot2")
> library(ggplot2)

just works!

Setting the repository

Every time you install a R package, you are asked which repository R should use. To set the repository and avoid having to specify this at every package install, simply:

• create a file .Rprofile in your home area.
• Add the following piece of code to it:


cat(".Rprofile: Setting UK repositoryn")
r = getOption("repos") # hard code the UK repo for CRAN
r["CRAN"] = "http://cran.uk.r-project.org"
options(repos = r)
rm(r)


I found this tip in a stackoverflow answer .

Qualification : Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application/ Life Science/ Biotechnology/ Agricultural Science or equivalent. Desirable: Knowledge of Statistical and Computational Genomics/ Proteomics/ Bioinformatics OR Post-Graduation in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application/ Life Science/ Biotechnology/ Agricultural Science or equivalent with 1st Division or 60% marks or equivalent with at least two years of research experience. Desirable:Expertise on use of various software/ tool.

No.of Post: 2

Emoluments for RA: Consolidated Rs. 24000/- per month + 30% HRA for Ph.D holders and consolidated Rs. 23000/- per month + 30% HRA for Master Degree.

Age Limit : Age should not be more than 40 years for the post of Research associate (5 years relaxation for SC/ST/ women candidates) and 3 years for OBC candidates as on date of interview.
How to apply

Interested candidates are invited to appear for Walk-In interview at Indian Agricultural Statistics Research Institute, Library Avenue, Pusa, New Delhi -110012, along with filled in application form , all the original certificates from matriculation onwards, Ph.D. or M.Sc. certificate (as the case may be) must be produced at the time of interview in either original or provisional, Bio-Data, attested copies of all experience certificates, testimonials etc., one passport size photograph and one set of the self-attested photocopies of all the required certificates from matriculation onwards and an attested copy of recent passport size photograph pasted onto the application form. Walk-in interview will be held on 16th April, 2015 at 10:30 a.m.

Click Here for Job Details & Application Form http://www.iasri.res.in/employment/employment.htm

Bioinformatics is full of opportunities. The sector is poised to open new avenues for the other related sectors also. But the biggest opportunity area in the Bioinformatics market will be in the drug discovery sector. Reduction of both the cost and time taken to discover a new drug due to fast development in the Bioinformatics tools and software zone is also making drug discovery an attractive field to venture in. Malaysian bioinformatics growth and future are discuss in this https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2723929/ paper. Keeping all such inportance in mind, following universities in Malaysia offering bioinformatics cources:

3 program(s) at AIMST University, Malaysia

Master of Science in Biotechnology (MSc) - Bioinformatics by Research

Master of Science (M.Sc) in Medical Microbiology (Bioinformatics) by Research

Doctor of Philosophy in Biotechnology (PhD) - Bioinformatics by Research

1 program(s) at INTI International University and Colleges, Malaysia

American Degree Transfer Program (Biosciences) in Bioinformatics

3 program(s) at Management and Science University (MSU), Malaysia

Master in Bioinformatics (By Research)

PhD in Bioinformatics

Bachelor in Bioinformatics (Hons)

1 program(s) at Multimedia University (MMU), Malaysia

Bachelor of Science (Honours) Bioinformatics

1 program(s) at Universiti Industri Selangor (UNISEL) Bestari Jaya Campus, Malaysia

Bachelor of Bioinformatics (Hons)

2 program(s) at Universiti Malaysia Sabah (UMS), Malaysia

PhD - Doctor of Philosophy in Bioinformatics (By Research)

MSc - Master of Science in Bioinformatics (By Research)

6 program(s) at Universiti Putra Malaysia (UPM), Malaysia

MSc - Master of Science in Bioinformatics by Research

Master of Science in Bioinformatics and System Biology by Research

Master of Science (M.Sc) in Bioinformatics and Systems Biology (With Thesis)

PhD - Doctor of Philosophy in Bioinformatics by Research

PhD - Doctor of Philosophy in Bioinformatics and Systems Biology (With Thesis)

PhD - Doctor of Philosophy in Bioinformatics and System Biology by Research

1 program(s) at Universiti Selangor (UNISEL), Malaysia

Bachelor of Bioinformatics (Hons)

3 program(s) at Universiti Teknologi Malaysia (UTM), Malaysia

M.Sc - Master of Science (Bioscience) in Bioinformatics Research Group (BIRG) By Research

PhD - Doctor of Philosophy (Bioscience) in Bioinformatics Research Group (BIRG) By Research

Bachelor of Computer Science (BioInformatics)

4 program(s) at University of Malaya (UM), Malaysia

MSc - Master of Science in Bioinformatics by Research

Master in Bioinformatics by Coursework

PhD - Doctor of Philosophy in Bioinformatics by Research

Bachelor of Science (BSc) in Bioinformatics

3 program(s) at Perdana University, Malaysia

Master in Bioinformatics (By Research)

PhD in Bioinformatics

Bachelor in Bioinformatics (Hons)

3 program(s) at Monash University, Malaysia

Master in Bioinformatics (By Research)

PhD in Bioinformatics

Bachelor in Bioinformatics (Hons)

The real bioinformatics scope lies if there are research labs which work in this field. One has to take account of that. If so then try to get information of those labs and visit them to get a hang of the work they pursue. For detail Bioinformatics in Malaysia: Hope, Initiative, Effort, Reality, and Challenges are discussed in https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2723929/ paper.

Candidates desirous of doing a short-term training / final year dissertation project for MSc (Life Sciences/Bioinformatics/Biotechnology or any science discipline) at UIAR Biophysics and Bioinformatics department may please drop an email atanju@iiar.res.in along with their resume.

Selected candidates will be further intimated. There will be a fees charged for doing the project at UIAR. The projects will be experimental or computational or involve both.

The training scope will be in the following areas but not limited to:

Bioinformatics analysis, Docking and Virtual screening, Molecular Dynamics simulation, Cloning, expression and purification of proteins, Biophysical and Biochemical characterisation of proteins, Crystallization and Structural Studies.

Advertisement: www.iiar.res.in/?q=node/450

Job Description

• Work within a fast-paced, collaborative environment with small project teams working on a variety of tasks ranging from new product development to DNA data processing
• Collaborate with Centrillion research scientists in order to bridge the gap between the laboratory and the digital world
• Develop tools to enable research projects to cope with the enormous amounts of data produced by modern DNA sequencing experiments
• Build simulation algorithms to help guide and analyze research done in the lab
• Solve challenging engineering problems that require the development of innovative algorithms

Requirements

• Strong background in mathematics/statistics with a degree in a related field
• Strong analytical, coding, communication, and organizational skills
• Experience with algorithm development, simulations, and data analysis
• Proficiency in at least one modern programming language (like Python or Perl)
• Experience analyzing genetic and biological data sets (e.g., DNA data analysis and image analysis)
• Experience with machine learning and pattern recognition is preferred

Please submit your resume at https://www.centrillionbio.com/career/ to apply for this position.