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Erik Clarke eclarke

  • Janssen Research & Development
  • Philadelphia, PA
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@eclarke
eclarke / beep.sh
Created Sep 15, 2018
sends a push with message contents given as arguments
View beep.sh
#!/bin/bash
curl --header 'Access-Token: <your_access_token_here>' \
--header 'Content-Type: application/json' \
--data-binary '{"body":":)","title":"$@","type":"note"}' \
--request POST \
https://api.pushbullet.com/v2/pushes
View keybase.md

Keybase proof

I hereby claim:

  • I am eclarke on github.
  • I am erikclarke (https://keybase.io/erikclarke) on keybase.
  • I have a public key ASDtTlFKxCJoOWfwfhHy-MJtbmGKnvzo-zxrJETJmi1kNQo

To claim this, I am signing this object:

View glmm.R
# This is the testing function that builds the models
testMixedEffects <- function(test.col) {
# We return this default in case of error/no fit
default <- list(null.model=NA, model=NA)
counts <- .mat[, colnames(.mat)==test.col]
if (sum(counts > 0)/length(counts) < sparsity) {
message(sprintf("%s: too sparse, skipping", test.col))
return(default)
}
@eclarke
eclarke / indicspecies_tutorial.R
Last active Jul 26, 2016
Using indicspecies with a melted data frame
View indicspecies_tutorial.R
# Using indicspecies with a melted data frame
# Their input is actually not hard to work with. First we need to re-create the count matrix.
# This creates a data frame with the sample ID and study group as the first two columns, then each column after that is an OTU name
# (Replace column names as appropriate)
mat <- melted.df %>% reshape2::dcast(SampleID + StudyGroup ~ otu)
# Next, we actually convert things into inputs
# Hadley's stuff hates rownames, so we have to remake them
rownames(mat) = mat$SampleID
@eclarke
eclarke / Makefile
Created Apr 20, 2016
Builds docs, html site, and pushes to github
View Makefile
docs:
Rscript -e "devtools::document(roclets=c('rd', 'collate', 'namespace', 'vignette'))"
gh-pages:
git checkout gh-pages
git merge master -X theirs -m "merge master"
site:docs gh-pages
Rscript -e "staticdocs::build_site(site_path='.', launch=FALSE)"
git commit -am 'updated docs'
@eclarke
eclarke / indvals.R
Last active Dec 4, 2015
Indicator species (indicator value) functions
View indvals.R
# Indicator value functions -----------------------------------------------
#' Returns the indicator value (Dufrene, 1997) for a given row of species counts
#' along with a vector of class assignments.
#' @param row: vector of counts (usually a row in a counts matrix)
#' @param class: which level in the grouping variable to test
#' @param classes: factor describing the grouping of the counts vector
.indval <- function(row, class, classes) {
idxs <- classes == class
A.ij <- sum(row[idxs]) / sum(row)
@eclarke
eclarke / diversity.R
Created Aug 18, 2015
Common diversity metrics
View diversity.R
alpha_diversity <- function(df, group.col, freq.col) {
# Returns a variety of diversity indices, including the Gini-Simpson index,
# the inverse Simpson index, and the Shannon-Weaver index. The SW index is
# calculated using the natural logarithm.
#
# Arguments:
# df: a data frame where the rows are species, with a column containing the
# grouping variable and another column containing the proportional
# abundances of each species
# group: the name of the column defining the grouping variable
View common_otus.fasta
>denovo1793
GGAGTCTGGGCCGTGTCTCAGTCCCAGTGTGGCCGATCACCCTCTCAGGTCGGCTATGTATCGTCGCCTTGGTGAGCCGTTACCCCACCAACTAGCTAATACAACGCAGGTCCATCTGGTAGTGATGCAATTGCACCTTTTAATTGACTATCATGCAATAGTCAATATTATGCGGTATTAGCTATCGTTTCCAATAGTTATCCCCCGCTACCAGGCAGGTTACCTACGCGTTACTCACCCGTTCGCAACTCATCCAGAGAAGCAAGCTCCTCCTTCAGCGTTCTACTTGCATGTATTAGGCACGCCGCCAGCGTTCGTC
>denovo2518
GGAGTTTGGGCCGTGTCTCAGTCCCAATGTGGCCGATCACCCTCTCAGGTCGGCTATGCATCACGGCCTTGGTGAGCCGTTACCTCACCAACTAGCTAATGCACCGCGGGTCCATCCATCAGCAGAAGCTTGCGCCTCTTTTCCTCTTCAAACCATGCGGTTCGAAGACCTATGCGGTTTTAGCATCCGTTTCCGAATGTTATCCCCCTCTGATGGGCAGGTTACCCACGTGTTACTCACCCGTTCGCCACTAGATTGACCAGTGCAAGCACCGGTCGCTCTCGTTCGACTTGCATGTATTAGGCACGCCGCCAGCGTTCGTC
>denovo271
GGAGTCTGGGCCGTGTCTCAGTCCCAGTGTGGCCGATCACCCTCTCAGGTCGGCTATGTATCGTCGCCTTGGTGAGCCGTTACCCCACCAACTAGCTAATACAACGCAGGTCCATCTGGTAGTGATGCAATTGCACCTTTTAAGCAAATGTCATGCAACATTTACTGTTATGCGGTATTAGCTATCGTTTCCAATAGTTATCCCCCGNTACCAGGCAGGTTACCTACGCGTTACTCACCCGTTCGCAACTCGTCCAGAAGAGCAAGCTCTCCCTTCAGCGTTCTACTTGCATGTATTAGGCACGCCGCCAGCGTTCGTC
>denovo3052
GGAGTCTGGTCCG
@eclarke
eclarke / named.py
Created Feb 12, 2015
Easy dot notation with a dictionary using a context manager
View named.py
# -*- coding: utf-8 -*-
"""
Uses a context manager to provide a dictionary as a 'namespace' of sorts,
allowing you to use dot notation to work with the dictionary. Example:
d = {'a': 5, 'b': 10}
with named(d) as n:
# prints 5
print n.a
# reassignment changes both n and d
@eclarke
eclarke / rendered-notebook.md
Created Oct 22, 2014
Rendered example notebook.org
View rendered-notebook.md

<2014-09-25 Thu>

Reading this (Wang et al. 2010), in particular Supp. report 4. Has to do with bootstrapping population estimates using the different enzymes used to find integration sites.

<2014-09-26 Fri>

Notes on (Wang et al. 2010) :popest:petersen:intsites: