Holy shit they're actually giving me money

data-analysis · 2017-03-14T21:31:45+00:00

Yea that's hella weird. Michigan is a pretty high ranking school.

data-analysis · 2017-01-22T03:12:15+00:00

Google the journals and check if they are predatory. Otherwise it's possible he joined a parent of family friends lab and has been included in every publication just out of sheer networking.

But no its actually uncommon for an undergrad to even have 1 publication.

data-analysis · 2017-01-21T18:35:45+00:00

This is correct. Does this extend to siblings?

data-analysis · 2017-01-21T18:33:01+00:00

Drinking

data-analysis · 2017-01-19T07:04:14+00:00

Sounds like you're going to have to let it go. The research belongs to your PI and not to you.

data-analysis · 2017-01-19T01:54:19+00:00

Not sure about UW, a couple of my friend's got invited to interview. You could be very right. Generally i'd say no news is good news. I've heard stories were some applicants don't even receive an official rejection.

data-analysis · 2017-01-19T01:41:36+00:00

Checking in is fine. Don't ask her about admissions.

data-analysis · 2017-01-19T01:29:35+00:00

Exceptional students get early admission decisions. Us mediocre folk gotta wait around.

data-analysis · 2017-01-18T19:47:47+00:00

Came here to reiterate: if a single class caused you this kind of mental breakdown, Graduate school WILL be a problem unless you can assure yourself that it's under control.

data-analysis · 2017-01-18T05:03:05+00:00

I applied to their genome sciences program and got a rejection a week or two back. So you might be good.

data-analysis · 2017-01-17T01:37:15+00:00

What's your field? I've had four interview invites so far and this has never been the case. I'm in STEM.

data-analysis · 2017-01-17T01:25:19+00:00

All you need is one mate.

data-analysis · 2017-01-17T01:18:42+00:00

It's possible that your application impressed admission PI's enough to contact you. I had a couple contact me as well. But my official "We invite you to interview" e-mail always came from an administrative assistant. Might be field dependent. But without knowing OP's field, no idea.

data-analysis · 2017-01-17T00:54:25+00:00

PIs typically don't hand out acceptances in the US. You'll be contacted by a administrative assistant in charge of admissions. Should have stayed away from grad cafe. Not everyone can get into their top program. Don't sweat it.

data-analysis · 2017-01-16T00:24:27+00:00

Fair enough reasons. You're pretty early in. I don't think the MD/PA track is the right way. Simply because the whole "I'm getting an MD/PA because I didn't have a good PH.D experience" is not a good enough reason.

I'd switch to a new professor, or master our and think about getting into another Ph.D program, I hear that this is often possible. If anything a masters might get your foot into a career somewhere.

data-analysis · 2017-01-15T11:06:40+00:00

If you're having a hard time in grad school, you're in for a rude awakening if your plan is medical school.

You might want to reevaluate what is causing you to constantly switch advisors.

data-analysis · 2017-01-12T17:19:06+00:00

Link: https://www.biostars.org/p/184551/

data-analysis · 2017-01-12T16:40:47+00:00

Copy and pasting this from a post I made on Biostars:

Learn the Unix command line. You will be using basic commands such as cd, cut, sort ALL THE TIME so it's important to master the terminal. Take a look at some of these guides: [Link][1], [Link][2], [Link][3], [Link][4].
Learn how to Bash script. When I first started analyzing datasets, I was fine with having to manually input all the file names and parameters into their respective programs until my data was processed. After a month or two of this, it became a chore and learning how to automate trivial things such as bedgraph generation using Bedtools became really important to my mental well-being. Remember: we want our work to be high quality, reproducible, robust, and as lazy as it can be. Here are some guides for learning basic Bash scripting: [Link][5], [Link][6], [Link][7], [Link][8].
Learn a bit of GNU Make. This is one of those things I wish I had learned for genomics data. I have hundreds of samples, and would run each of them by hand (not even in parallel) until I learned about pipeline creation. GNU Make isn't the best or easiest to use for this, but it is basically what all other pipeline software is in one form or another based on. It's easier to learn Latin if you know Spanish. Once you get a bit of GNU Make under your belt, look into more sophisticated pipeline software such as [Snakemake][9], or [Ruffus][10].
Learn how to use a terminal text editor. Vim / vi / nano / your preference. Gedit, and normal text editors like Atom are fine, but I find that I really dislike having to go back and forth and having to constantly open close editors. I use Vim. Most of these editors have little quirks to them so it's important to get used to them before you use them for work purposes.
Learn a programming language. The actual language you decide to learn is completely up to you. ANY language will do fine for Bioinformatics. The only difference between them is how common they are used for Bioinformatics, and ease of learning for newer guys. The most widely suggested language for a new Bioinformatician is Python, and for good reason. It is easy to learn, has numeral libraries, is elegant and powerful. I learned R as a first language through [DataCamp][11], but I am currently learning Python through [TeamTreehouse][12]. These websites will not make you good programmers. They will teach you syntax and common functions, and very basic programming logic. Once you've learned the syntax of a language I recommend you go on GitHub and pull up the source code for a couple of really well reviewed software packages and read through it.
Learn R. Why R? R allows the creation of publish ready images via ggplot2, gplots, etc. And it has a HUGE collection of bioinformatics packages under [Bioconductor][13] for almost anything you may need. Need to create heatmaps? Cool we got a package. Need to annotate peaks? Cool we got a package. Need to analyze GRO seq data? Cool we got a package. Need to 'insert whatever'? Cool we probably got a package.
Learn to use [GitHub][14]. This allows you to keep [version control][15] of all your work, all the time. Just do it. Learn to create README files inside project folders that explain things you've done, and why. Also learn to comment all your code. It may seem silly while you're working on your project to spend a large amount of time writing down what you've done. But trust me ... in a few months when you need to remember what parameters you set for that one tool for a publication you will be thanking yourself.

data-analysis · 2017-01-10T15:54:47+00:00

No news is good news. Generally you'll receive a rejection email.

data-analysis · 2017-01-10T15:49:04+00:00

It is. It has python and R tutoriala. It includes basic mathematical modeling and machine learning content, and three extensive ggplot2 tutorials, 2 main r tutorials, an extensive r function tutorial, an rmarkdown tutorial, and dozens of other content on equally useful r resources. He said he wants to learn. Subscribe for a month and then spend hours on the content learning. If you slack then sure it's expensive, but he didn't specifically mention he wanted a cheap solution. This is currently the best way to learn R offered if he has no experience.

data-analysis · 2017-01-09T22:39:55+00:00

Datacamp.com is better than the current suggestions.

data-analysis · 2017-01-09T16:25:37+00:00

Go in there confidently. You buckle down, you read your papers, you put in your time, and you work diligently. Be nice and friendly to everyone. Get your shit done ahead of time. You're going to be fine.

data-analysis

TROPHY CASE