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Cell Ranger 2.1 (latest), printed on 04/09/2018

Cell Ranger is a set of analysis pipelines that process Chromium single-cell RNA-seq output to align reads, generate gene-cell matrices and perform clustering and gene expression analysis. Cell Ranger includes four pipelines relevant to single-cell gene expression experiments:

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demultiplexes raw base call (BCL) files generated by Illumina sequencers into FASTQ files. It is a wrapper around Illumina's bcl2fastq, with additional useful features that are specific to 10x libraries and a simplified sample sheet format.

cellranger mkfastq

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takes FASTQ files from cellranger mkfastq and performs alignment, filtering, barcode counting, and UMI counting. It uses the Chromium cellular barcodes to generate gene-barcode matrices, determine clusters, and perform gene expression analysis. The count pipeline can take input from nike free run 50 black friday
on the same library.

cellranger count

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aggregates outputs from multiple runs of cellranger count , normalizing those runs to the same sequencing depth and then recomputing the gene-barcode matrices and analysis on the combined data. The aggr pipeline can be used to combine data from multiple samples into an experiment-wide gene-barcode matrix and analysis.

cellranger aggr

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takes gene-barcode matrices produced by cellranger count or cellranger aggr and reruns the dimensionality reduction, clustering, and gene expression algorithms using tunable parameter settings.

cellranger reanalyze

These pipelines combine Chromium-specific algorithms with the widely used RNA-seq aligner STAR. Output is delivered in standard BAM, MEX, CSV, HDF5 and HTML formats that are augmented with cellular information.

Throughout the documentation, you will see references to samples , libraries and sequencing runs . We define these as follows:

Sample Library Sequencing Run Flowcell

The relationship between these terms can be complex:

How to Transpose Data in Excel: Turn Rows into Columns

How to Transpose Data in Excel: Turn Rows into Columns (vice versa)

Reorganizing data in a spreadsheet can be a pain. Especially when you have to make big changes that a nike sneaker roshe run flyknit triple
won’t fix.

One of the common tasks that fall into this category is transposing—turning rows into columns, or columns into rows.

Without any special help from Excel, that takes a long time. But Excel has some built-in transposing capabilities that make the process easier.

NEW: I've just released brand-new FREE Excel training. You learn about formulas and functions. It's perfect for the beginner .

Let’s take a look at turning rows into columns (and vice versa) in Excel, as well as a few of the things you’ll need to keep in mind when you do so.

If you want to really use Excel’s power for displaying rows and columns, check out pivot tables .

They’re one of Excel’s best features.

Kasper Langmann

Table of Contents

Chapter 1: Chapter 2: Chapter 3:

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Chapter 4:

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Chapter 5:

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Chapter 6:

Chapter 7: Wrapping things up…

Chapter 7: Defining transposition

Before we start, let’s make sure we know exactly what transposing is.

In short, transposing is taking a row and turning it into a column, or a column and turning it into a row . Some people call this “rotating” a row or column.

row and turning it into a column, or a column and turning it into a row

The leftmost cell in a row will always become the topmost cell in a column, and the topmost cell in a column will always become the leftmost cell in a row.

This ensures that column and row labels are always in the right place.

There are a couple ways we can transpose data in Excel. Before we get into them, grab the free sample workbook so you can try it yourself!

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