Merge pull request #132 from mribeirodantas/fix-readme

Fix README shields / zenodo info

README.md

@@ -3,6 +3,7 @@
 [![GitHub Actions CI Status](https://github.com/nf-core/scrnaseq/workflows/nf-core%20CI/badge.svg)](https://github.com/nf-core/scrnaseq/actions?query=workflow%3A%22nf-core+CI%22)
 [![GitHub Actions Linting Status](https://github.com/nf-core/scrnaseq/workflows/nf-core%20linting/badge.svg)](https://github.com/nf-core/scrnaseq/actions?query=workflow%3A%22nf-core+linting%22)
 [![AWS CI](https://img.shields.io/badge/CI%20tests-full%20size-FF9900?logo=Amazon%20AWS)](https://nf-co.re/scrnaseq/results)
+[![Cite with Zenodo](http://img.shields.io/badge/DOI-10.5281/zenodo.3568187-1073c8)](https://doi.org/10.5281/zenodo.3568187)
 [![Cite with Zenodo](http://img.shields.io/badge/DOI-10.5281/zenodo.6656322)](https://doi.org/10.5281/zenodo.6656322)
 
 [![Nextflow](https://img.shields.io/badge/nextflow%20DSL2-%E2%89%A521.10.3-23aa62.svg)](https://www.nextflow.io/)
@@ -15,8 +16,6 @@
 [![Follow on Twitter](http://img.shields.io/badge/twitter-%40nf__core-1DA1F2?logo=twitter)](https://twitter.com/nf_core)
 [![Watch on YouTube](http://img.shields.io/badge/youtube-nf--core-FF0000?logo=youtube)](https://www.youtube.com/c/nf-core)
 
-[![Join us on Slack](https://img.shields.io/badge/slack-nfcore/scrnaseq-blue.svg)](https://nfcore.slack.com/channels/scrnaseq)
-
 ## Introduction
 
 **nf-core/scrnaseq** is a bioinformatics best-practice analysis pipeline for processing 10x Genomics single-cell RNA-seq data.
@@ -83,7 +82,7 @@ For further information or help, don't hesitate to get in touch on the [Slack `#
 
 ## Citations
 
-If you use nf-core/scrnaseq for your analysis, please cite it using the following doi: [10.5281/zenodo.3568187](https://doi.org/10.5281/10.5281/zenodo.3568187)
+If you use nf-core/scrnaseq for your analysis, please cite it using the following doi: [10.5281/zenodo.3568187](https://doi.org/10.5281/zenodo.3568187)
 
 The basic benchmarks that were used as motivation for incorporating the three available modular workflows can be found in [this publication](https://www.biorxiv.org/content/10.1101/673285v2).