BOL: Related items

Postdoctoral Position (Bioinformatics/Computational Biology)

Thu, 12 Dec 2013 17:58:00 -0600

University College Cork
LAPTI
Cork-Co Cork-Ireland

Postdoctoral position is available for three years to work on development of Bioinformatics resources for the analysis and visualization of ribosome profiling data. Ribosome profiling (ribo-seq) is a technology that allows mapping positions of the ribosomes on the whole transcriptome level with a nucleotide precision. The technology allows obtaining high resolution digital snapshots of gene expression in cells. The position is available starting on the 1st of October, 2013.

Candidate is expected to have Ph.D. in Bioinformatics or Computational Biology. Candidates with the degree in non-Biological disciplines such as Computer Science, Statistics, Applied Mathematics, Physics or Electrical Engineering will also be considered.

The position is available at LAPTI (http://lapti.ucc.ie) that is located in the Western Gate Building (http://www.stwarchitects.com/project-information.php?c=1&p=09993) at University College Cork. Western Gate Building Research Complex hosts several UCC departments and provides ideal environment for interdisciplinary research. Cork (sometimes referenced as “Venice of Ireland”) is the second most populous city in the Republic. It has friendly cosmopolitan atmosphere and vibrant culture. A number of American industrial giants such as Apple , EMC and Pfizer have chosen Cork as a home for their European headquarters.

The details of the application process are given at http://lapti.ucc.ie/jobs.html. To ensure prompt processing of your application use the subject line: ‘Postdoc computational’. All applications received prior to August the 1st are guaranteed equal consideration. However, applications at the later dates will also be considered until the position is filled.

For more info visit http://lapti.ucc.ie

Figeno: Tool for plotting sequencing data along genomic coordinates.

LEGE — Tue, 17 Sep 2024 02:28:15 -0500

Tool for plotting sequencing data along genomic coordinates.

FIGENO is a
  FIGure
    GENerator
for GENOmics

With figeno, you can plot various types of sequencing data along genomic coordinates. Video overview: https://www.youtube.com/watch?v=h1cBeXoSYTA.

Address of the bookmark: https://github.com/CompEpigen/figeno

Critical to discoveries in bioinformatics

Mon, 16 Dec 2013 17:13:24 -0600

EMBL-EBI distributes datasets worldwide using the Janet network. This biological data enables the discovery of new drugs, new diagnostics and increasingly new agro-chemicals. Their work, which includes the 1000-genome project, has generated petabytes of data and this growth is showing no signs of abating. On-demand bandwidth over Janet will therefore be critical to their ongoing work.

Import R Data

Abhimanyu Singh — Wed, 12 Jul 2017 08:30:46 -0500

It is often necessary to import sample textbook data into R before you start working on your homework.

Excel File

Quite frequently, the sample data is in Excel format, and needs to be imported into R prior to use. For this, we can use the function read.xls from the gdata package. It reads from an Excel spreadsheet and returns a data frame. The following shows how to load an Excel spreadsheet named "mydata.xls". This method requires Perl runtime to be present in the system.

> library(gdata)                   # load gdata package
> help(read.xls)                   # documentation
> mydata = read.xls("mydata.xls")  # read from first sheet

Alternatively, we can use the function loadWorkbook from the XLConnect package to read the entire workbook, and then load the worksheets with readWorksheet. The XLConnect package requires Java to be pre-installed.

> library(XLConnect) # load XLConnect package
> wk = loadWorkbook("mydata.xls")
> df = readWorksheet(wk, sheet="Sheet1")

Minitab File

If the data file is in Minitab Portable Worksheet format, it can be opened with the function read.mtp from the foreign package. It returns a list of components in the Minitab worksheet.

> library(foreign)                 # load the foreign package
> help(read.mtp)                   # documentation
> mydata = read.mtp("mydata.mtp")  # read from .mtp file

SPSS File

For the data files in SPSS format, it can be opened with the function read.spss also from the foreign package. There is a "to.data.frame" option for choosing whether a data frame is to be returned. By default, it returns a list of components instead.

> library(foreign) # load the foreign package
> help(read.spss) # documentation
> mydata = read.spss("myfile", to.data.frame=TRUE)

Table File

A data table can resides in a text file. The cells inside the table are separated by blank characters. Here is an example of a table with 4 rows and 3 columns.

100   a1   b1
200   a2   b2
300   a3   b3
400   a4   b4

Now copy and paste the table above in a file named "mydata.txt" with a text editor. Then load the data into the workspace with the function read.table.

> mydata = read.table("mydata.txt")  # read text file
> mydata                             # print data frame
   V1 V2 V3
1 100 a1 b1
2 200 a2 b2
3 300 a3 b3
4 400 a4 b4

For further detail of the function read.table, please consult the R documentation.

> help(read.table)

CSV File

The sample data can also be in comma separated values (CSV) format. Each cell inside such data file is separated by a special character, which usually is a comma, although other characters can be used as well.

The first row of the data file should contain the column names instead of the actual data. Here is a sample of the expected format.

Col1,Col2,Col3
100,a1,b1
200,a2,b2
300,a3,b3

After we copy and paste the data above in a file named "mydata.csv" with a text editor, we can read the data with the function read.csv.

> mydata = read.csv("mydata.csv")  # read csv file
> mydata
  Col1 Col2 Col3
1  100   a1   b1
2  200   a2   b2
3  300   a3   b3

In various European locales, as the comma character serves as the decimal point, the function read.csv2 should be used instead. For further detail of the read.csv and read.csv2 functions, please consult the R documentation.

> help(read.csv)

Working Directory

Finally, the code samples above assume the data files are located in the R working directory, which can be found with the function getwd.

> getwd() # get current working directory

You can select a different working directory with the function setwd(), and thus avoid entering the full path of the data files.

> setwd("") # set working directory

Note that the forward slash should be used as the path separator even on Windows platform.

> setwd("C:/MyDoc")

Research Associate @ INDIAN INSTITUTE OF SPICES RESEARCH

Wed, 25 Dec 2013 12:34:43 -0600

INDIAN INSTITUTE OF SPICES RESEARCH
(Indian Council of Agricultural Research)
Marikunnu P.O., Kozhikode – 673 012, Kerala

WALK -IN- TEST CUM INTERVIEW

Walk- in- Test cum Interview (based on test) for the selection of Research Associate (Bioinformatics) & Bioinformatic Trainees under the scheme ‘Distributed Information Sub Centre- DISC’ will be held at this Institute as per details indicated below.

Research Associate

Date of Interview : 21 -01-2014 at 10.00 A.M

Qualifications : a) Essential: Doctorate degree in Bioinformatics or Biotechnology/Life Sciences/Biochemistry with expertise in Bioinformatics as evidenced by publications.

Three years research experience after MVSc/MPharm/ME/MTech with Bioinformatics Specialization.

b Desirable: Experience in handling NGS data Programming skills in Python/Bioperl

Emoluments : Rs:22000/- per month + HRA (higher pay upto Rs.24000/- can be paid depending on the qualifications and experience.

Upper age limit : 40 years for Men & 45 years for Women as on date of Interview (Upper Age limits are relaxable for SC, ST and OBC candidates as per Govt. of India norms (at present 5 years for SC/ST and 3 years for OBC)

Duration of Project : Till the closure of the project.

General Terms and conditions

1. The above positions are purely on temporary basis and is co-terminus with the closure of the project. There is no provision of re-employment after termination of project. The selected candidate will not have any right for claiming pay scale or absorption against any regular post being vacant on a later date at this Institute.
2 . No TA/DA will be paid for attending the Interview.
3. Canvassing in any form will lead to cancellation of candidate.
4. The decision of Director, IISR would be final and binding in all aspects.
5. Candidates will not be permitted to enter the Examination Hall after 10.00 A.M.
6. Candidates who secure the minimum marks prescribed by the Institute in written test only will be eligible for calling for the interview. The number of candidates to be called for the interview will be decided by the Director of the Institute.
7 Those who do not possess original Degree/PG certificate or Provisional certificate will not be allowed to attend the Test/Interview.

Note: 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.
Location of IISR Kozhikode Main Campus - Pallithazham bus stop between Moozhikkal East and Chelavoor on the NH 212 ”Kozhikode - Kollegal” Road.

Advertisement: www.spices.res.in/pdf/DISC-Website.pdf

lordFAST: sensitive and Fast Alignment Search Tool for LOng noisy Read sequencing Data

BioJoker — Tue, 27 Nov 2018 04:43:57 -0600

lordFAST is a sensitive tool for mapping long reads with high error rates. lordFAST is specially designed for aligning reads from PacBio sequencing technology but provides the user the ability to change alignment parameters depending on the reads and application.

lordFAST, a novel long-read mapper that is specifically designed to align reads generated by PacBio and potentially other SMS technologies to a reference. lordFAST not only has higher sensitivity than the available alternatives, it is also among the fastest and has a very low memory footprint.

Address of the bookmark: https://github.com/vpc-ccg/lordfast

The genome factory !!!

Madhvan Reddy — Thu, 16 Jan 2014 02:09:31 -0600

Illumina, Inc. announced Tuesday that its new HiSeq X Ten Sequencing System has broken the “sound barrier” of human genomics by enabling the $1,000 genome. “This platform includes dramatic technology breakthroughs that enable researchers to undertake studies of unprecedented scale by providing the throughput to sequence tens of thousands of human whole genomes in a single year in a single lab,” Illumina stated.

Initial customers for the HiSeq X Ten System, which will ship in Q1 2014, include Macrogen, based in Seoul, South Korea and its CLIA laboratory in Rockville, Maryland, the Broad Institute in Cambridge, Massachusetts, and the Garvan Institute of Medical Research in Sydney, Australia.

“For the first time, it looks like it will be possible to deliver the $1,000 genome, which is tremendously exciting,” said Eric Lander, founding director of the Broad Institute and a professor of biology at MIT. “The HiSeq X Ten should give us the ability to analyze complete genomic information from huge sample populations. Over the next few years, we have an opportunity to learn as much about the genetics of human disease as we have learned in the history of medicine.”

“The HiSeq X Ten is an ideal platform for scientists and institutions focused on the discovery of genotypic variation to enable a deeper understanding of human biology and genetic disease,” Illumina stated. “It can sequence tens of thousands of samples annually with high-quality, high-coverage sequencing, delivering a comprehensive catalog of human variation within and outside coding regions.”

HiSeq X Ten utilizes a number of advanced design features to generate massive throughput. Patterned flow cells, which contain billions of nanowells at fixed locations, combined with a new clustering chemistry deliver a significant increase in data density (6 billion clusters per run). Using state-of-the art optics and faster chemistry, HiSeq X Ten can process sequencing flow cells more quickly than ever before — generating a 10x increase in daily throughput when compared to current HiSeq 2500 performance.

The HiSeq X Ten is sold as a set of 10 or more ultra-high throughput sequencing systems, each generating up to 1.8 terabases (Tb) of sequencing data in less than three days or up to 600 gigabases (Gb) per day, per system, providing the throughput to sequence tens of thousands of high-quality, high-coverage genomes per year. Illumina says the $1,000 includes typical instrument depreciation, DNA extraction, library preparation, and estimated labor.

Comparative Genomics Data Set Including 240 Mammals Released !

Jit — Thu, 19 Nov 2020 06:45:39 -0600

The genome of 130 mammals was sequenced by a large international consortium and the data was analyzed together with 110 existing genomes to allow scientists to identify the important positions in the DNA. This report, published in Nature today will help advance research on human disease mutations and inform how best to protect endangered species.

In addition to the knowledge of the human genome, all these genomes, widely sampled across mammals, can be used to research how particular organisms respond to different conditions. Some otters, for example, have a thick, water-resistant shell, and some rodents, but not all, have adapted to hibernation. These animal traits will help us to understand human traits, such as metabolic diseases.

With climate change and more animal ecosystems being threatened by human activity, the protection of endangered species is becoming increasingly important. Scientists have historically researched several people in various populations of a species to understand the genetic variation that occurs in that species. This is important for understanding how particular species can be protected. In this study, animals on the Red List of Endangered Species of the International Union for Conservation of Nature had fewer differences in their genomes, which is consistent with their endangered status.

Ref @ A comparative genomics multitool for scientific discovery and conservation https://www.nature.com/articles/s41586-020-2876-6

Data at http://zoonomiaproject.org/

Senior Research Fellow @ Indian Agricultural Statistics Research Institute

Thu, 23 Jan 2014 06:22:15 -0600

Indian Agricultural Statistics Research Institute
Library Avenue, Pusa, New Delhi – 110012

Walk-in-Interview

Walk-in-interview will be held on February 11, 2014 at 10:00 A.M. at IASRI, New Delhi for a project “Whole Genome Sequencing and Development of Allied Genomics Resources in Two Commercially Important Fish-Labeo rohita and Clarias batrachus” funded by Department of Biotechnology, Ministry of Science and Technology, Government of India, New Delhi for the following posts. The appointment will be on contractual basis upto September, 2016 or till the termination of the project whichever is earlier and the incumbent shall not have any claim for regular appointment under ICAR.

Senior Research Fellow Two

Post-Graduation in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application/ Biotechnology or equivalent with 1st Division

 Knowledge of Statistical Analysis /Bioinformatics tools/computer programming for computational genomics.

Emoluments for Research Associate: Consolidated Rs: 16000/- per month + 30% HRA (1st Two years) and Rs: 18000/- per month + 30% HRA (3rd Year)

Age Limit: Age should be not more than 35 years (5 years relaxation for SC/ST/women candidates and 3 years for OBC candidates as on date of interview).
Interested candidates are requested to appear for Walk-in-Interview on the date and time as specified above in Room No. 106, Training Cum Administrative Block of the Institute along with their application giving bio-data with attested copies of certificates, degrees, testimonials, etc. and one passport size photograph. Original certificates/ Degrees are needed to be produced at the time of interview. No T.A. /D.A. will be paid for appearing in the interview.

Advertisement: http://www.iasri.res.in/employment/2014/srf_cabin.pdf

Fundamentals of Data Visualization by Claus O. Wilke

Abhi — Sat, 08 Jun 2024 16:07:19 -0500

The book is meant as a guide to making visualizations that accurately reflect the data, tell a story, and look professional. It has grown out of my experience of working with students and postdocs in my laboratory on thousands of data visualizations. Over the years, I have noticed that the same issues arise over and over. I have attempted to collect my accumulated knowledge from these interactions in the form of this book.

The entire book is written in R Markdown, using RStudio as my text editor and the bookdown package to turn a collection of markdown documents into a coherent whole. The book’s source code is hosted on GitHub, at https://github.com/clauswilke/dataviz.

Address of the bookmark: https://clauswilke.com/dataviz/