nhaliday + libraries   131

Use and Interpretation of LD Score Regression
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies: https://sci-hub.bz/10.1038/ng.3211
- Po-Ru Loh, Nick Patterson, et al.

https://www.biorxiv.org/content/biorxiv/early/2014/02/21/002931.full.pdf

Both polygenicity (i.e. many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield inflated distributions of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from bias and true signal from polygenicity. We have developed an approach that quantifies the contributions of each by examining the relationship between test statistics and linkage disequilibrium (LD). We term this approach LD Score regression. LD Score regression provides an upper bound on the contribution of confounding bias to the observed inflation in test statistics and can be used to estimate a more powerful correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of test statistic inflation in many GWAS of large sample size.

Supplementary Note: https://images.nature.com/original/nature-assets/ng/journal/v47/n3/extref/ng.3211-S1.pdf

An atlas of genetic correlations across human diseases
and traits: https://sci-hub.bz/10.1038/ng.3406

https://www.biorxiv.org/content/early/2015/01/27/014498.full.pdf

Supplementary Note: https://images.nature.com/original/nature-assets/ng/journal/v47/n11/extref/ng.3406-S1.pdf

https://github.com/bulik/ldsc
ldsc is a command line tool for estimating heritability and genetic correlation from GWAS summary statistics. ldsc also computes LD Scores.
nibble  pdf  slides  talks  bio  biodet  genetics  genomics  GWAS  genetic-correlation  correlation  methodology  bioinformatics  concept  levers  🌞  tutorial  explanation  pop-structure  gene-drift  ideas  multi  study  org:nat  article  repo  software  tools  libraries  stats  hypothesis-testing  biases  confounding  gotchas  QTL  simulation  survey  preprint  population-genetics 
november 2017 by nhaliday
Ancient Admixture in Human History
- Patterson, Reich et al., 2012
Population mixture is an important process in biology. We present a suite of methods for learning about population mixtures, implemented in a software package called ADMIXTOOLS, that support formal tests for whether mixture occurred and make it possible to infer proportions and dates of mixture. We also describe the development of a new single nucleotide polymorphism (SNP) array consisting of 629,433 sites with clearly documented ascertainment that was specifically designed for population genetic analyses and that we genotyped in 934 individuals from 53 diverse populations. To illustrate the methods, we give a number of examples that provide new insights about the history of human admixture. The most striking finding is a clear signal of admixture into northern Europe, with one ancestral population related to present-day Basques and Sardinians and the other related to present-day populations of northeast Asia and the Americas. This likely reflects a history of admixture between Neolithic migrants and the indigenous Mesolithic population of Europe, consistent with recent analyses of ancient bones from Sweden and the sequencing of the genome of the Tyrolean “Iceman.”
nibble  pdf  study  article  methodology  bio  sapiens  genetics  genomics  population-genetics  migration  gene-flow  software  trees  concept  history  antiquity  europe  roots  gavisti  🌞  bioinformatics  metrics  hypothesis-testing  levers  ideas  libraries  tools  pop-structure 
november 2017 by nhaliday
What is the best way to parse command-line arguments with Python? - Quora
- Anders Kaseorg

Use the standard optparse library.

It’s important to uphold your users’ expectation that your utility will parse arguments in the same way as every other UNIX utility. If you roll your own parsing code, you’ll almost certainly break that expectation in obvious or subtle ways.

Although the documentation claims that optparse has been deprecated in favor of argparse, which supports more features like optional option arguments and configurable prefix characters, I can’t recommend argparse until it’s been fixed to parse required option arguments in the standard UNIX way. Currently, argparse uses an unexpected heuristic which may lead to subtle bugs in other scripts that call your program.

consider also click (which uses the optparse behavior)
q-n-a  qra  oly  best-practices  programming  terminal  unix  python  libraries  protocol  gotchas  howto  pls  yak-shaving  integration-extension 
august 2017 by nhaliday
Broadcasting — NumPy v1.13 Manual
When operating on two arrays, NumPy compares their shapes element-wise. It starts with the trailing dimensions, and works its way forward. Two dimensions are compatible when

they are equal, or
one of them is 1
If these conditions are not met, a ValueError: frames are not aligned exception is thrown, indicating that the arrays have incompatible shapes. The size of the resulting array is the maximum size along each dimension of the input arrays.

Arrays do not need to have the same number of dimensions. For example, if you have a 256x256x3 array of RGB values, and you want to scale each color in the image by a different value, you can multiply the image by a one-dimensional array with 3 values.
python  libraries  programming  howto  protocol  numerics  pls  linear-algebra 
august 2017 by nhaliday
Welcome to wbdata’s documentation! — wbdata 0.2.7 documentation
Wbdata is a simple python interface to find and request information from the World Bank’s various databases, either as a dictionary containing full metadata or as a pandas DataFrame. Currently, wbdata wraps most of the World Bank API, and also adds some convenience functions for searching and retrieving information.
data  metrics  econ-metrics  objektbuch  libraries  python  documentation  yak-shaving  api  hmm  world  developing-world  sleuthin  maps  programming  reference 
february 2017 by nhaliday
Decison Tree for Optimization Software
including convex programming

Mosek makes out pretty good but not pareto-optimal
benchmarks  optimization  software  libraries  comparison  data  performance  faq  frameworks  curvature  convexity-curvature 
november 2016 by nhaliday
Why xkcd-style graphs are important - Chris Stucchio
A: lowering expectations
and apparently matplotlib has this visualization built-in
rhetoric  dataviz  libraries  python  howto  techtariat 
november 2016 by nhaliday
I don't understand Python's Asyncio | Armin Ronacher's Thoughts and Writings
Man that thing is complex and it keeps getting more complex. I do not have the mental capacity to casually work with asyncio. It requires constantly updating the knowledge with all language changes and it has tremendously complicated the language. It's impressive that an ecosystem is evolving around it but I can't help but get the impression that it will take quite a few more years for it to become a particularly enjoyable and stable development experience.

What landed in 3.5 (the actual new coroutine objects) is great. In particular with the changes that will come up there is a sensible base that I wish would have been in earlier versions. The entire mess with overloading generators to be coroutines was a mistake in my mind. With regards to what's in asyncio I'm not sure of anything. It's an incredibly complex thing and super messy internally. It's hard to comprehend how it works in all details. When you can pass a generator, when it has to be a real coroutine, what futures are, what tasks are, how the loop works and that did not even come to the actual IO part.

The worst part is that asyncio is not even particularly fast. David Beazley's live demo hacked up asyncio replacement is twice as fast as it. There is an enormous amount of complexity that's hard to understand and reason about and then it fails on it's main promise. I'm not sure what to think about it but I know at least that I don't understand asyncio enough to feel confident about giving people advice about how to structure code for it.
python  libraries  review  concurrency  programming  pls  rant  🖥  techtariat  intricacy 
october 2016 by nhaliday
Spaceship Generator | Hacker News
some interesting discussion of the value of procedural generation in the comments
commentary  hn  graphics  games  programming  libraries  repo  oss  project  SIGGRAPH 
june 2016 by nhaliday
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