Nils Gehlenborg ngehlenborg

name

figures

Title of the Vignette

name	file
The messy title	clean_file.json

name	file
Oh how beautiful	nice-figure.json

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Gosling Data Transformation Example

Filter reads from an indexed BAM file based on MAPQ score

Created with help by @sehilyi

Single-cell epigenomic analyses implicate candidate causal variants at inherited risk loci for Alzheimer’s and Parkinson’s diseases

Corces et al., Nature Genetics (2020)

Figure 4B

Comparison of Micro-C and Hi-C for HFFc6 Cells

Source: http://mirnylab.mit.edu/projects/microc/

Gosling.js Example w/o HiGlass Server

For many file formats Gosling can parse the data directly from a web server without the need to request tiles from a HiGlass server. The list of "serverless" file formats can be found here:

https://github.com/gosling-lang/gosling-docs/blob/master/docs/Data.md#plain-datasets

State	Awards	Funding	Winner	Population	Non_Hispanic_White	Hispanic_or_Latino	Black	American_Indian_or_Alaskan_Native	Asian	Native_Hawaiian_or_Pacific_Islander	Mixed_race
Alabama	654	294964217	Trump	4822023	67	3.9	26.2	0.6	1.1	0.1	1.5
Alaska	17	14594777	Trump	731449	64.1	5.5	3.3	14.8	5.4	1	7.3
Arizona	382	163447535	Trump	6553255	57.8	29.6	4.1	4.6	2.8	0.2	3.4
Arkansas	108	96652655	Trump	2949131	74.5	6.4	15.4	0.8	1.2	0.2	2
California	7720	3686026589	Clinton	38041430	40.1	37.6	6.2	1	13	0.4	4.9
Colorado	991	349974172	Clinton	5187582	70	20.7	4	1.1	2.8	0.1	3.4
Connecticut	1179	510609681	Clinton	3590347	71.2	13.4	10.1	0.3	3.8	0	2.6
Delaware	75	45371848	Clinton	917092	65.3	8.2	21.4	0.5	3.2	0	2.7
District Of Columbia	361	214175791	Clinton	632323	34.8	9.1	50.7	0.3	3.5	0.1	2.9

HiC data

Smaller test set

Real data set

FILENAME=rao_et_al/HMEC/5kb_resolution_intrachromosomal/chr1/MAPQGE30/chr1_5kb.RAWobserved
FILENAME=rao_et_al/HMEC/5kb_resolution_intrachromosomal/chr1/MAPQGE30/chr1_5kb.RAWobserved
FILENAME=rao_et_al/HUVEC/5kb_resolution_intrachromosomal/chr1/MAPQGE30/chr1_5kb.RAWobserved

	1 9990 10541 NA_peak_1 659 . 14.0891 71.6944 65.9622 122
	1 17416 17558 NA_peak_2 57 . 3.78096 8.53598 5.75775 82
	1 28990 29391 NA_peak_3 110 . 5.55909 14.2035 11.0904 153
	1 136792 137016 NA_peak_4 43 . 3.89551 6.96678 4.30427 137
	1 137351 137493 NA_peak_5 31 . 3.52146 5.7373 3.17432 82
	1 180683 180998 NA_peak_6 148 . 5.32793 18.1263 14.81 236
	1 181424 181576 NA_peak_7 79 . 3.93461 10.8354 7.90908 84
	1 184442 184558 NA_peak_8 48 . 3.06671 7.58896 4.8773 62
	1 199522 200072 NA_peak_9 158 . 6.6282 19.2684 15.8945 374
	1 267946 268070 NA_peak_10 36 . 3.66636 6.25752 3.65471 61

	# Uninsured persons estimates for ACA
	# Centers for Disease Control and Prevention National Health Interview Survey
	# https://www.cdc.gov/nchs/data/nhis/earlyrelease/insur201702.pdf
	# (see Table II, page A3)

	# ACA data estimates through 2016: absolute uninsured
	aca_data <- approx(c(2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2020, 2026),
	c(48.6,46.3,45.5,44.8,36,28.6,28.2,28.2,28.2,28.2,28.2), n=17)

	# Uninsured persons estimates for AHCA from Congressional Budget Office