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Dr. Seok's Bioinformatics Datasets, First Steps

The raw file you downloaded,
opened with your own hands

The figures in a paper are results somebody else has already finished drawing. The real learning is upstream of them. Download GSE268555 from GEO and what you are actually holding is four .h5 files โ€” with 40,100 cells and 32,285 genes inside them. How do you open that, and what do you look at first?
These 20 lessons begin at the moment you open that one file. Python runs right inside this page.

๐Ÿ Python๐Ÿ—„๏ธ HDF5๐Ÿงฎ sparse matrices ๐Ÿงน quality control๐Ÿ“‰ PCA & t-SNE๐ŸŽจ sliding gallery๐Ÿ‡ฌ๐Ÿ‡ง English
Start lesson 1 โ†’

How you'll learn

๐Ÿ“ฆWith the real file

Not an imitation. 1,200 cells ร— 32,285 genes, cut straight out of the original h5 deposited at GEO as GSE268555, opened by you with h5py.

๐Ÿ”Structure first

What to check the moment a file lands in your hands โ€” groups, datasets, shapes, dtypes, compression. You get the order in which you read somebody else's file into your fingers.

๐ŸŽจTaking it in as pictures

A table of numbers tells you nothing. The sliding gallery widget lets you page through sixteen views of this dataset and see the whole of it in thirty seconds.

โš ๏ธThe failures too

The moment memory blows up, the moment gene names collide, the moment a batch effect fools you โ€” you live through the accidents that really happen in advance.

Full curriculum

01
ํŒŒ์ผ ๋„ค ๊ฐœ๊ฐ€ ๋„์ฐฉํ–ˆ๋‹ค โ€” ๋…ผ๋ฌธ์˜ ๊ทธ๋ฆผ์€ ์—ฌ๊ธฐ์„œ ์‹œ์ž‘ํ•œ๋‹ค
GEO ๋“ฑ๋ก๋ฒˆํ˜ธ ์ฝ๊ธฐ ยท ๋ฌด์—‡์„ ๋ฐ›์•˜๋Š”์ง€ ํ™•์ธํ•˜๊ธฐ
โœ“
02
์ƒ์ž๋ฅผ ์—ฌ๋Š” ๋ฒ• โ€” HDF5 ์•ˆ์—๋Š” ํด๋”๊ฐ€ ๋“ค์–ด ์žˆ๋‹ค
h5py ๋กœ ์—ด๊ณ  ยท ๊ตฌ์กฐ๋ฅผ ํ†ต์งธ๋กœ ํ›‘๊ธฐ
โœ“
03
๋ชจ์–‘๋ถ€ํ„ฐ ๋ณธ๋‹ค โ€” ํ–‰์ด ์œ ์ „์ž์ธ๊ฐ€ ์„ธํฌ์ธ๊ฐ€
shape ยท dtype ยท ๊ทธ๋ฆฌ๊ณ  ๋ฉ”๋ชจ๋ฆฌ ๊ณ„์‚ฐ
โœ“
04
96%๊ฐ€ 0์ด๋‹ค โ€” ํฌ์†Œํ–‰๋ ฌ ์‚ผ์ด์‚ฌ๋ฅผ ์ฝ๋Š”๋‹ค
data ยท indices ยท indptr ์ด ์–ด๋–ป๊ฒŒ ํ–‰๋ ฌ์ด ๋˜๋Š”๊ฐ€
โœ“
05
์ด๋ฆ„ํ‘œ ์ฝ๊ธฐ โ€” ์œ ์ „์ž ์ด๋ฆ„์€ ์ƒ๊ฐ๋ณด๋‹ค ์œ„ํ—˜ํ•˜๋‹ค
features(idยทnameยทtype) ยท barcodes ยท ์ค‘๋ณต ์ด๋ฆ„์˜ ํ•จ์ •
โœ“
06
์„ธํฌ ํ•œ ๊ฐœ๋ฅผ ๊บผ๋‚ด ๋ณธ๋‹ค โ€” ์ˆซ์ž์— ์ฒ˜์Œ์œผ๋กœ ๋œป์ด ์ƒ๊ธฐ๋Š” ์ˆœ๊ฐ„
ํ•œ ์„ธํฌ์˜ ์ƒ์œ„ ๋ฐœํ˜„ ์œ ์ „์ž ยท ๊ทธ๋ฆฌ๊ณ  ์ด์ƒํ•œ ์ด๋ฆ„๋“ค
โœ“
07
๋‚˜์œ ์„ธํฌ๋ฅผ ๊ณจ๋ผ๋‚ธ๋‹ค โ€” ๋ฌธํ„ฑ์€ ์–ด๋–ป๊ฒŒ ์ •ํ•˜๋Š”๊ฐ€
์ด UMI ยท ๊ฒ€์ถœ ์œ ์ „์ž ์ˆ˜ ยท ๋ฏธํ† ์ฝ˜๋“œ๋ฆฌ์•„ ๋น„์œจ
โœ“
08
๋ฌด๋ฆŽ ๊ทธ๋ž˜ํ”„ โ€” ๋‚จ์ด ์ด๋ฏธ ๋‚ด๋ฆฐ ๊ฒฐ์ •์„ ์•Œ์•„๋ณธ๋‹ค
barcode rank ยท raw ์™€ filtered ์˜ ์ฐจ์ด ยท ์ฃผ๋ณ€ RNA
โœ“
09
ํฌ๊ธฐ๋ฅผ ๋งž์ถ˜๋‹ค โ€” ์ •๊ทœํ™” ์—†์ด๋Š” ์•„๋ฌด๊ฒƒ๋„ ๋น„๊ตํ•  ์ˆ˜ ์—†๋‹ค
CP10K ยท log1p ยท ๊ทธ๋ฆฌ๊ณ  ์™œ ๋กœ๊ทธ๋ฅผ ์”Œ์šฐ๋Š”๊ฐ€
โœ“
10
2,000๊ฐœ๋งŒ ๋‚จ๊ธด๋‹ค โ€” ๋ชจ๋“  ์œ ์ „์ž๊ฐ€ ์ •๋ณด๋ฅผ ์ฃผ์ง€๋Š” ์•Š๋Š”๋‹ค
ํ‰๊ท -๋ถ„์‚ฐ ์ถ”์„ธ ยท ๊ณ ๋ณ€๋™ ์œ ์ „์ž(HVG)
โœ“
11
์ถ•์„ ๊ฐˆ์•„ ๋ผ์šด๋‹ค โ€” 2,000์ฐจ์›์„ 30์ฐจ์›์œผ๋กœ
ํ‘œ์ค€ํ™” ยท ์ฃผ์„ฑ๋ถ„ ยท ๋ช‡ ๊ฐœ๋ฅผ ๋‚จ๊ธธ ๊ฒƒ์ธ๊ฐ€
โœ“
12
๋น„์Šทํ•œ ์„ธํฌ๋ผ๋ฆฌ ๋ฌถ๋Š”๋‹ค โ€” k ๋Š” ๋ช‡์œผ๋กœ ํ• ๊นŒ
k-ํ‰๊ท  ยท ํ•ด์ƒ๋„ ยท ๊ทธ๋ฆฌ๊ณ  ์ •๋‹ต์ด ์—†๋‹ค๋Š” ์‚ฌ์‹ค
โœ“
13
2์ฐจ์› ์ง€๋„ โ€” t-SNE์™€ UMAP์€ ๋ฌด์—‡์„ ๋ณด์—ฌ ์ฃผ๊ณ  ๋ฌด์—‡์„ ์ˆจ๊ธฐ๋Š”๊ฐ€
์ฐจ์› ์ถ•์†Œ ์‹œ๊ฐํ™” ยท ๊ฑฐ๋ฆฌ ํ•ด์„์˜ ํ•จ์ •
โœ“
14
์ด๋ฆ„์„ ๋ถ™์ธ๋‹ค โ€” ๊ตฐ์ง‘ 3๋ฒˆ์€ ๋ฌด์Šจ ์„ธํฌ์ธ๊ฐ€
ํ‘œ์ง€์ž ์œ ์ „์ž ยท ์ ๊ทธ๋ฆผ ยท ๊ทธ๋ฆฌ๊ณ  ์ˆœํ™˜๋…ผ์ฆ์˜ ํ•จ์ •
โœ“
15
์Šฌ๋ผ์ด๋”ฉ ๊ฐค๋Ÿฌ๋ฆฌ โ€” ๋ฐ์ดํ„ฐ์…‹ ํ•˜๋‚˜๋ฅผ 30์ดˆ์— ํ›‘๋Š”๋‹ค
ํƒ์ƒ‰์  ์ž๋ฃŒ ๋ถ„์„์˜ ์ˆœ์„œ๋ฅผ ๋ชธ์— ์ตํžˆ๊ธฐ
โœ“
16
๋„ค ์กฐ๊ฑด์„ ๋น„๊ตํ•œ๋‹ค โ€” ๋…ผ๋ฌธ์˜ ๊ฒฐ๋ก ์ด ์ •๋ง ์ž๋ฃŒ์— ์žˆ๋Š”๊ฐ€
์„ธํฌ ๊ตฌ์„ฑ๋น„ ยท ๊ทธ๋ฆฌ๊ณ  ์ƒ์ฅ ํ•œ ๋งˆ๋ฆฌ๋ผ๋Š” ํ•œ๊ณ„
โœ“
17
์–ด๋–ค ์œ ์ „์ž๊ฐ€ ๋‹ฌ๋ผ์กŒ๋‚˜ โ€” ํ™”์‚ฐ๋„์™€ ๊ทธ ์•ˆ์˜ ํ•จ์ •
์ฐจ๋“ฑ๋ฐœํ˜„ ยท ์œ ์‚ฌ๋ณต์ œ ยท ์œ ์‚ฌ๋ฒŒํฌ(pseudobulk)
โœ“
18
์†์ง€ ์•Š๋Š” ๋ฒ• โ€” ์›์ž๋ฃŒ๊ฐ€ ํŒŒ ๋†“์€ ํ•จ์ • ์—ฌ๋Ÿ ๊ฐœ
๋ฐฐ์น˜ํšจ๊ณผ ยท ์ด์ค‘์„ธํฌ ยท ์ฃผ๋ณ€ RNA ยท ์„ฑ๋ณ„ ยท ์ˆœํ™˜๋…ผ์ฆ
โœ“
19
๋‚จ์ด ๋‹ค์‹œ ๋Œ๋ฆด ์ˆ˜ ์žˆ๊ฒŒ โ€” ๋ฐ˜๋…„ ๋’ค์˜ ๋‚˜๋ฅผ ์œ„ํ•ด
ํด๋” ๊ตฌ์กฐ ยท ๋ฒ„์ „ ๊ณ ์ • ยท ๋‚œ์ˆ˜ ์”จ์•— ยท ์ฒดํฌ์„ฌ
โœ“
20
์šฐ๋ฆฌ๊ฐ€ ๋ณธ ๊ฒƒ๊ณผ ๋ชป ๋ณธ ๊ฒƒ โ€” ๊ทธ๋ฆฌ๊ณ  ๋‹ค์Œ ๋ฐ์ดํ„ฐ์…‹์œผ๋กœ
20๊ฐ•์˜ ์ •๋ฆฌ ยท ์ด ์ž๋ฃŒ์˜ ํ•œ๊ณ„ ยท ๋‹ค์Œ์— ์—ด์–ด ๋ณผ ํŒŒ์ผ๋“ค
โœ“